Research Paper
Management and Entrepreneurship
Younos Vakil Alroaia
Abstract
The aim of this study is providing a developed model for SMEs' in open innovation activities. In this regard, an appropriate model was defined by studying the literature. Then, after selecting a sample of 60 small and medium enterprises the data were collected by a questionnaire and were analyzed with ...
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The aim of this study is providing a developed model for SMEs' in open innovation activities. In this regard, an appropriate model was defined by studying the literature. Then, after selecting a sample of 60 small and medium enterprises the data were collected by a questionnaire and were analyzed with the Smart PLS software. In the third stage, the relative importance of factors was tested from the perspective of 10 experts in the field of open innovation along with experienced managers of the small and medium enterprises with more than 15 years of work experience with the help of ANP and PROMETHEE methods. The results showed that these factors include the parameters: Product Characteristics, Inter-organizational Factors, and Environmental Factors. In addition, the most important factors include Product Characteristics. Finally, several implications were made such as changing the degree of SMEs' participation in open innovation activities over time according to continuous monitoring of these moderators.
SI:Big Data and Artificial Intelligence (BDAI)
Case studies in industry and services
Najaf Ghrachorloo; Faramarz Nouri; Mostafa Javanmardi; Houshang Taghizadeh
Abstract
In the past years, East Azerbaijan Province in Iran has always been at the top of the number of incidents in the country in the reports related to the annual analysis of incidents of domestic natural gas subscribers. Despite planning and spending at the expense of previous years, there has been no significant ...
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In the past years, East Azerbaijan Province in Iran has always been at the top of the number of incidents in the country in the reports related to the annual analysis of incidents of domestic natural gas subscribers. Despite planning and spending at the expense of previous years, there has been no significant reduction in incident statistics. The purpose of this article is to investigate the root factors affecting the occurrence of incidents in domestic consumers of natural gas in East Azerbaijan province and to provide control and reduction strategies for incidents. To study the statistical analysis of natural gas-related incidents, the big data mining data approach of natural gas incidents in East Azerbaijan province during the years 2014 to 2020 besides Pareto analysis, root analysis, and Delphi have been used. The results of data and information analysis indicate that the most important technical factors affecting the bite are: lack of proper installation of the chimney, use of non-standard chimneys, leakage due to seams between the chimney parts, / the presence of cracks, and virtual blockage of the chimney.
Research Paper
Case studies in industry and services
Rasoul Jamshidi; Sattar Rajabpour Sanati; Morteza Zarrabi
Abstract
The saving banks of “umbilical cord blood stem cells” are considered as strategic health-based institutions in most countries. Due to the limited capacity of cord blood sample storage tanks, the samples should be evaluated according to their quality. So these banks need a method to assess ...
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The saving banks of “umbilical cord blood stem cells” are considered as strategic health-based institutions in most countries. Due to the limited capacity of cord blood sample storage tanks, the samples should be evaluated according to their quality. So these banks need a method to assess quality. In this paper, first, the effective factors on the quality index of the extracted cord blood from newborn infants are identified using the electronic records and database of Royan’s umbilical cord blood bank. Then by machine learning and various statistical methods such as multilayer perceptron neural networks, radial basis function neural networks, logistic regression, and C4.5 decision tree, the quality value of blood samples and their proper category (for discarding or freezing) are determined. Two different sets of data have been used to evaluate the proposed methods. The results show that the ensemble of radial basis function neural network with k-means clustering model has the best accuracy compared to other methods, which categorizes the samples with 91.5% accuracy for the first data set and 81.6% accuracy for the second one. The results also show that using this method can save about $1 million annually.
Research Paper
Management and Entrepreneurship
Abbas Heravi; Afsaneh Zamani Moghadam; Seyed Ahmad Hashemi; Younos Vakil Alroaia; Abddulah Sajadi Jagharg
Abstract
Given the increased competition and turbulence in business environments, the proper management of human resources and employee growth is a significant challenge faced by organizations to achieve competitive advantage. The present study aimed to analyze the influential factors in human resource development ...
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Given the increased competition and turbulence in business environments, the proper management of human resources and employee growth is a significant challenge faced by organizations to achieve competitive advantage. The present study aimed to analyze the influential factors in human resource development (HRD) in state-owned enterprises (SOEs). This was an applied research in terms of objective and a mixed (qualitative-quantitative), exploratory study in terms of design. In the qualitative-quantitative section of the study, content analysis and descriptive-exploratory techniques were applied. Data were collected via semi-structured interviews and by using questionnaires in the qualitative and quantitative sections, respectively. The research population included human resource experts, managers, and experts in the field of human resource planning and SOE management. In total, 22 individuals were selected via purposeful sampling. In the qualitative section, data analysis was carried out using open, axial, and selective coding for the classification of the identified factors into four categories of organizational, occupational, behavioral, and empowerment factors. In addition, screening was performed using the Fuzzy Delphi method, and the correlations between the identified factors and sub-factors were determined using the Fuzzy DEMATEL method. According to the results, empowerment factors were the most significant determinants of HRD, which could be improved by considering the associated influential factors and prioritization of organizational factors. On the other hand, the factor weighting findings based on the fuzzy analytic network process indicated that among the identified factors and sub-factors of knowledge management, empowerment factors had the most significant impact on HRD.
Research Paper
Statistical Process
Nastaran Hajarian; farzad Movahedi Sobhani; Seyed Jafar Sadjadi
Abstract
One of the most complex and costly systems in the industry is the Gas turbine (GT). Because of the complexity of these assets, various indicators have been used to monitor the health condition of different parts of the gas turbine. Turbine exit temperature (TET) spread is one of the significant indicators ...
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One of the most complex and costly systems in the industry is the Gas turbine (GT). Because of the complexity of these assets, various indicators have been used to monitor the health condition of different parts of the gas turbine. Turbine exit temperature (TET) spread is one of the significant indicators that help monitor and detect faults such as overall engine deterioration and burner fault. The goal of this article is to use data-driven approaches to monitor TET data to detect faults early, as fault detection can have a significant impact on gas turbine reliability and availability. In this study, the TET data of v94.2 GT is measured by six temperature transmitters to show a detailed profile. According to the statistical tests, TET data are high dimensional and time-dependent in the real world industry. Hence, three distinctive methods in the field of the gas turbine are proposed in this study for early fault detection. Conventional principal component analysis (PCA), moving window PCA (MWPCA), and incremental PCA (IPCA) were implemented on TET data. According to the results, the conventional PCA model is a non-adaptive method, and the false alarm rate is high due to the incompatibility of this approach and the process. The MWPCA based on V-step-ahead and IPCA approaches overcame the non-stationary problem and reduced the false alarm rate. In fact, these approaches can distinguish between the normal time-varying and slow ramp fault processes. The results showed that IPCA could detect fault situations faster than MWPCA based on V-step-ahead in this study.
SI: RAIDSCM
Transportation
Sarow Saeedi; Omid Poursabzi; Zaniar Ardalan; Sajad Karimi
Abstract
Hub location problems (HLP) have multiple applications in logistic systems, the airways industry, supply chain network design, and telecommunication. In the HLP, the selected nodes as hubs perform the principal role in processing the inflow arising from other nodes. So, congestion would be inevitable ...
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Hub location problems (HLP) have multiple applications in logistic systems, the airways industry, supply chain network design, and telecommunication. In the HLP, the selected nodes as hubs perform the principal role in processing the inflow arising from other nodes. So, congestion would be inevitable at hub nodes. This paper considers a p-hub median problem with multiple hub node servers delivering service at variable rates. Since the service rates are limited and variable, a queue is formed at each hub server. To tackle this problem, we developed a mixed-integer linear programming model that optimizes the selected hub nodes to reduce congestion under an allowable defined queue length at each server and minimize the total costs of the model, including transportation and hub establishment costs. We utilized the Civil Aeronautics Board (CAB) dataset containing 25 USA cities, which is a valuable source for designing numerical examples in the HLP, to prove the model's efficiency. The results obtained from the designed sample problems show that strategic decisions on defining the number of hubs and maximum acceptable queue length at each hub server will significantly impact the hub location network design.
SI: ADLRTCA
Information Retrieval
Ali Fallahi RahmatAbadi; Javad Mohammadzadeh
Abstract
With the exponentially increasing volume of online data, searching and finding required information have become an extensive and time-consuming task. Recommender Systems as a subclass of information retrieval and decision support systems by providing personalized suggestions helping users access what ...
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With the exponentially increasing volume of online data, searching and finding required information have become an extensive and time-consuming task. Recommender Systems as a subclass of information retrieval and decision support systems by providing personalized suggestions helping users access what they need more efficiently. Among the different techniques for building a recommender system, Collaborative Filtering (CF) is the most popular and widespread approach. However, cold start and data sparsity are the fundamental challenges ahead of implementing an effective CF-based recommender. Recent successful developments in enhancing and implementing deep learning architectures motivated many studies to propose deep learning-based solutions for solving the recommenders' weak points. In this research, unlike the past similar works about using deep learning architectures in recommender systems that covered different techniques generally, we specifically provide a comprehensive review of deep learning-based collaborative filtering recommender systems. This in-depth filtering gives a clear overview of the level of popularity, gaps, and ignored areas on leveraging deep learning techniques to build CF-based systems as the most influential recommenders.
SI:RSSCMMA
Supply chain management
Mohammad Reza Razdan; Saeed Aghasi; Sayyed Mohammad Reza Davoodi
Abstract
Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, ...
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Supply chain risk management involves identifying, ranking, and adopting appropriate strategies to control and deal with risks that could disrupt chain performance. These risks can be caused by different issues and descriptions and surveys about these risks are associated with uncertainty, ambiguity, qualitativeness and incomplete and sometimes contradictory information. Therefore, their ranking needs the techniques that can model the mentioned issues. neutrosophic logic makes it possible to model propositions with uncertainty, incomplete information, ambiguity, qualitativeness, and even inconsistency. Accordingly, the approach of the present study is to use a combined method of neutrosophic hierarchical analysis and TOPSIS for ranking the risk. Core of this paper is proposed a hybrid decision making method for identification and ranking of supply chain management by a Neutrosophic analytical hierarchy process and TOPSIS approach. The case study is Mobarakeh Steel Company of Isfahan and three criteria including resilience, agility and robustness are considered as major strategies to deal with risk and seventeen risk-related issues are ranked as options. The results show that government constraints, economic and environmental risks, inventory shortages, technology risk, forecast risk and financial (cash) problems are the most important risks threatening the supply chain. Therefore, we believe that the proposed framework provides managers with valuable knowledge for decision making.
SI:Big Data and Artificial Intelligence (BDAI)
Data mining
amir daneshvar; Fariba Salahi; Maryam Ebrahimi; Bijan Nahavandi
Abstract
The aim of analyzing passengers' behavioral patterns is providing support for transportation management. In other words, to improve services like scheduling, evacuation policies, and marketing, it is essential to understand spatial and temporal patterns of passengers' trips. Smart Card Automated Fare ...
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The aim of analyzing passengers' behavioral patterns is providing support for transportation management. In other words, to improve services like scheduling, evacuation policies, and marketing, it is essential to understand spatial and temporal patterns of passengers' trips. Smart Card Automated Fare Collection System (SCAFCS) makes it possible to utilize data mining tools for the purpose of passengers' behavioral pattern analysis. The specific goal of this research is to obtain functional information for passenger's behavioral pattern analysis in city express bus which is called BRT, and classification of passengers to improve performance of bus fast transportation system. Additionally, it is attempted to predict usage and traffic status in a line through predicting passenger's behavior in a bus line. In this paper, smart card data is applied to provide combinational algorithms for clustering and analysis based on data mining. To this end, we have used a combination of data mining methods and particle swarm optimisation algorithm and leveraged multivariate time series prediction to estimate behavioral patterns. Results show that price and compression ratio features are the most influencing features in the separability of transportation smart card data. According to obtained Pareto front, four features include a card identification number, bus identification number, bus line number, and charge times are influencing clustering criteria.
Research Paper
production planning
ommolbanin yousefi; saeed Rezaeei Moghadam; neda hajheidari
Abstract
One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps ...
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One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps the decision makers to make such decisions. The proposed model comprises four main objectives, the first one of which considers minimizing costs (including costs of manufacturing product, supplying, maintenance, inventory stock shortage, and expenditures related to man power). The second objective is defined as maximizing customers’ satisfaction. Minimizing suppliers’ satisfaction makes up the third objective and maximizing the quality of the manufactured products constitutes the fourth objective. In this model, the demand parameter is investigated under uncertain conditions; hence, other parameters influenced by this parameter are also presented under uncertain conditions occurring within three differing scenarios. This model is solved through LP- metric and the LINGO v14.0.1.55 software. At first the model is solved by means of numerical example; then it is solved by the actual data that are related to a military industry. Finally, process, variables like inventory level, overtime work hours etc, are valued with the help of closed-loop supply chain of the proposed model.
Research Paper
Computational modelling
Samaneh Akbarpour; Abdollah Shidfar; Hashem Saberi Najafi
Abstract
In this article, a mathematical model of the inverse problem is considered. Basedon this model a formulation of inverse problem for heat equation is proposed.Shifted Chebyshev Tau (SCT) method is suggested to solve the inverse problem. The aim of this determined effort is to identify unknown function ...
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In this article, a mathematical model of the inverse problem is considered. Basedon this model a formulation of inverse problem for heat equation is proposed.Shifted Chebyshev Tau (SCT) method is suggested to solve the inverse problem. The aim of this determined effort is to identify unknown function and unknown control parameter of the mathematical model. In order to achieve highly accuratesolution to this problem, the operational matrix of shifted Chebyshev polynomialsis investigated in conjunction with tau scheme. To demonstrate the validity andapplicability of the developed scheme, numerical example is presented.
Review Paper
Heuristics and Metaheuristics Algorithms
Mehdi Khadem; Abbas Toloie Eshlaghy; kiamars Fathi Hafshejani
Abstract
Over the past decade, solving complex optimization problems with metaheuristic algorithms has attracted many experts and researchers.There are exact methods and approximate methods to solve optimization problems. Nature has always been a model for humans to draw the best mechanisms and the best engineering ...
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Over the past decade, solving complex optimization problems with metaheuristic algorithms has attracted many experts and researchers.There are exact methods and approximate methods to solve optimization problems. Nature has always been a model for humans to draw the best mechanisms and the best engineering out of it and use it to solve their problems. The concept of optimization is evident in several natural processes, such as the evolution of species, the behavior of social groups, the immune system, and the search strategies of various animal populations. For this purpose, the use of nature-inspired optimization algorithms is increasingly being developed to solve various scientific and engineering problems due to their simplicity and flexibility. Anything in a particular situation can solve a significant problem for human society. This paper presents a comprehensive overview of the metaheuristic algorithms and classifications in this field and offers a novel classification based on the features of these algorithms.
SI: RAIDSCM
Supply chain management
Mona Beiranvand; Sayyed mohammad reza Davoodi
Abstract
Today, one of the topics in supply chain management is "multiple sales channels" and "pricing". In this research, a food producer (west Sahar Dasht Company) has been selected, and several retailers and wholesalers have been considered as the company's customers. This research dynamically solves the model ...
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Today, one of the topics in supply chain management is "multiple sales channels" and "pricing". In this research, a food producer (west Sahar Dasht Company) has been selected, and several retailers and wholesalers have been considered as the company's customers. This research dynamically solves the model through the game theory method. To obtain the equilibrium point and Stockelberg, the lower level optimal values (retailers and suppliers) are calculated based on the higher-level values (manufacturer), which turns the multi-level model into a single-level model to calculate the higher level optimal values. By presenting a case study and analyzing the sensitivity of the parameters, it was shown that some changes in the parameters have a significant effect on the problem variables, and its equilibrium model is better. Because game theory is proposed to solve problems on a small scale, and because the present problem is so complex, genetic algorithm meta-heuristic and particle aggregation optimization have been used to solve medium and large problems. To validate their results, they are compared with the results obtained from the mathematical model. Finally, comparing the performance of the two meta-heuristic algorithms through statistical analysis has shown that the particle aggregation optimization algorithm performs better than the genetic algorithm.
Research Paper
Supply chain management
Meysam Donyavi Rad; Ehsan Sadeh; Zeinolabedin Amini Sabegh; Reza Ehtesham Rasi
Abstract
The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management ...
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The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management cycle will reduce potential damage at the time of the disaster and reduce the vulnerability of society. Therefore, in this research, a mathematical model of crisis logistics planning considering the problem of primary and secondary crisis in disaster relief is introduced, which is the innovation of this research. In the primary crisis, the goal is to provide services and relief goods to crisis areas, and in the second stage, the secondary crisis that occurs after the primary crisis seeks to provide relief to crisis centers and transfer the injured to relief centers. Therefore, this research proposes a mathematical fuzzy ideal programming model in two primary and secondary crises. In the primary crisis, the goal is to provide services and relief goods to crisis-stricken areas. The secondary crisis, which occurs after the primary crisis, aims to support crisis-stricken centers and move injured people to relief bases in the second step. According to the proposed model, Bertsimas-Sim’s fuzzy programming that formulation proposed by Bertsimas and Sim (B&S) [1] and robust approach we initially used. The Epsilon constraint method was used to solve the low-dimensional model. Multi-objective meta-heuristic algorithms have been designed to handle the computational complexity of large-scale real-time problems. Multiple comparisons and analyses have been proposed to assess the performance of the model and problem-solving capabilities. The results indicate that the proposed approach can be applied and implemented to develop a real-world humanitarian logistics network.
Research Paper
Game theory
Elham Sadat Mousavi; Ashkan Hafezalkotob; Ahmad Makui; Mohammad Kazem Sayadi
Abstract
This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader ...
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This paper presents an optimization model for hotel pricing in the competitive environment following the Covid-19 epidemic, in which the government intervenes by offering appropriate tariffs and hotels use incentive policies such as discounts to attract customers. we consider the government as the leader and the hotels as the followers of the Stalkberg model, then apply the Nash equilibrium to determine the optimal price and demand of hotels in competitive conditions, taking into account the discount. By considering a government utility function, the optimal level of government tariffs is determined. The results indicate that government intervention in the tourism industry includes measures that benefit tourism. Because the government can increase the hotel revenue and expand tourism in favor of hoteliers by reducing its profits. Extensive analysis has been performed on five-star, four-star, and three-star hotels in a tourist area in Iran, and some of the most important managerial insights have been explained.
Research Paper
Case studies in industry and services
AYYAPPAN - S
Abstract
To enhance the manufacturing process capability of a refractory company, the scope for implementing the Lean Six Sigma (LSS) methodology is analyzed in this work. The DMAIC methodology of Six Sigma is used in this project to determine the Critical to Quality Characteristics (CTQs), defining the possible ...
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To enhance the manufacturing process capability of a refractory company, the scope for implementing the Lean Six Sigma (LSS) methodology is analyzed in this work. The DMAIC methodology of Six Sigma is used in this project to determine the Critical to Quality Characteristics (CTQs), defining the possible causes, identifying the variation in sources, establishing the variable relationships, and implementing the control plans. It was found from the DMAIC approach that the quality of Raw Crude, Water Content, and the frequency of using Temperature Calibration Equipment are the main factors responsible for lowering Productivity in Shaft Kiln. To improve the productivity of Kiln, it was suggested to process the raw crude free of mud, remove the moisture content present in the magnesite stones and take action on changing the frequency of measuring the oil feeding calibration equipment.
SI:RSSCMMA
Risk management
Mohammad Reza Alijanzadeh; Seyed Ahmad Shayannia; Mohammad Mehdi Movahedi
Abstract
One of the methods that has been widely used by researchers in analyzing the risk of net operations is the analysis of the effect and failure modes in order to identify critical failure modes and focus planning and net resources on them. In analyzing the effect and failure modes, one of the most important ...
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One of the methods that has been widely used by researchers in analyzing the risk of net operations is the analysis of the effect and failure modes in order to identify critical failure modes and focus planning and net resources on them. In analyzing the effect and failure modes, one of the most important steps is the process of prioritizing the equipment in order to determine the critical equipment, as well as determining the critical failure modes and prioritizing them in order to purposefully plan the net operation. The purpose of this paper is to dynamically rank equipment in intuitive fuzzy environments with interval values in order to identify and prioritize critical equipment and to present a mathematical model for combining optimization of preventive maintenance intervals and control parameters. For this purpose, a model is presented that calculates the dynamic weights of each equipment according to the conditions of each equipment in the indicators of failure probability, failure consequence and lack of fault detection power, and therefore dynamic ranking is provided for the equipment. In this research, for dynamic prioritization of equipment, the method of analysis of the ratio of intuitive fuzzy gradual weighting with quantitative values (IVIF-SWARA) was presented. Then, a mathematical model was presented for the identified critical equipment. The proposed model can determine the optimal value of each of the four decision variables, ie sample size, inspection rotation time, control limit coefficient and preventive repair intervals of each of the critical equipment of the Northern Oil Pipeline and Telecommunication Company and the total expected cost of integration per unit. Minimize time. The results show that the proposed model is much more flexible in calculating the weight and dynamic rating of equipment and provides more logical rating results.
Research Paper
Case studies in industry and services
Robert S Keyser; Parisa Pooyan
Abstract
Root cause analysis techniques are often applied to problems in the workplace; however, they may also prove very useful to home projects. This research explores the application of two root cause analysis techniques in home projects: (1) 5 Whys to determine the root cause of a home air conditioning unit ...
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Root cause analysis techniques are often applied to problems in the workplace; however, they may also prove very useful to home projects. This research explores the application of two root cause analysis techniques in home projects: (1) 5 Whys to determine the root cause of a home air conditioning unit that runs continuously but does not cool, and (2) an innovative Lean PFMEA to repair a John Deere riding mower that starts, then stops. Employing the 5 Whys technique led to the discovery of incorrect color-coded wiring from the original air conditioning unit to the thermostat. Lean PFMEA enabled a correct diagnosis and resolution of the mower start/stop issue via a Kaizen event, grass clippings in the fuel line, which was remedied by cleaning the fuel tank and replacing the fuel lines, fuel filter, and carburetor. These techniques provide Lean methodological approaches to problem-solving, which often leads to reduced homeowner aggravation, repair time, and repair expense.
Research Paper
Human factors, ergonomics, and safety
Silas Oseme Okuma; Akpofure Avwerosuoghene Enughwure
Abstract
The purpose of this research is to investigate the safety of inland waterway transportation in Kurutie, Okerenkoko, and Escravos River, Nigeria. The study used a cross-sectional research design, and the study's target group includes passengers who are technical experts, maritime workers, non-academic, ...
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The purpose of this research is to investigate the safety of inland waterway transportation in Kurutie, Okerenkoko, and Escravos River, Nigeria. The study used a cross-sectional research design, and the study's target group includes passengers who are technical experts, maritime workers, non-academic, academic personnel's and students of Nigeria Maritime University, and self-employed passengers who live in the study locations. Questionnaires and field observations were used to obtain data. 378 questionnaires were delivered throughout the study area. According to the study, most cases of maritime boat mishaps beleaguered the inland waterway in the study area due to unskilled boat drivers, overloading/overcrowding of boats, and a lack of enforcement of safety laws by government agencies within the study area. The study recommended that relevant authorities, such as the Nigeria Inland Waterways Authority, enforce safety regulations among jetty operators and boat drivers; that training and certifying boat drivers are enforced; and that government involvement be increased by developing a sensitization program to educate passengers on the importance of adhering to safety practices along the waterways.
Research Paper
Data Envelopment Analysis, DEA
Reza Fallahnejad; Sanaz Asadi Rahmati; Kayvan Moradipour
Abstract
To evaluate the performance and estimate the efficiency of decision-making units (DMUs) in Data Envelopment Analysis (DEA), the available data are used. These data are usually divided into two categories of inputs and outputs based on their natures. If the price data is also available for inputs, it ...
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To evaluate the performance and estimate the efficiency of decision-making units (DMUs) in Data Envelopment Analysis (DEA), the available data are used. These data are usually divided into two categories of inputs and outputs based on their natures. If the price data is also available for inputs, it is necessary to calculate another type of the efficiency called cost effi-ciency. Since the efficiency of units in such a framework is depended on the both quantities of inputs and outputs and also the prices of inputs, it is important to find the sources of cost inefficiency related to each of the factors and plans to ad-dress them. In this paper, we intend to present a new decomposition of cost efficiency and observed cost versus optimal cost, which are arised from each of the factors involved in the cost inefficiency, in a non-competitive pricing environment which the input price vector for different DMUs can be different. Moreover, for the first time, in parallel with using the PPS based on input and output quantities and introducing some cost inefficiency factors related to this set, we will intro-duce new sets called price and cost production sets that the first is based on the prices of inputs and output factors, and the second is based on the optimal vectors of inputs and prices obtained from two previous PPS, and then we will introduce other factors of cost inefficiency in the sets. Accordingly, new decomposition for cost inefficiencies will be presented. Also, in the previous analyzes, congestion inefficiency has not been considered as one of the important factors in cost inefficiency. In this study, we also intend to consider the impact of this factor on cost efficiency.
Research Paper
Decision analysis and methods
Elham Ebrahimi; Mohammad Reza Fathi; Seyed Mohammad Sobhani
Abstract
Multiple criteria decision-making (MCDM) is well known nowadays as a methodology in which a set of techniques are integrated to evaluate a set of alternatives with specified criteria for the purpose of selecting or ranking. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is ...
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Multiple criteria decision-making (MCDM) is well known nowadays as a methodology in which a set of techniques are integrated to evaluate a set of alternatives with specified criteria for the purpose of selecting or ranking. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is well-established methodology frequently considered in MCDM analyses. TOPSIS has a sound logic that represents the rationale of human choice and is a scalar value simultaneously taking into account both the best and worst alternatives. Moreover, it has a simple computation process that could be easily programmed and finally it has the ability to rank alternatives on attributes to be visualized on a polyhedron, in at least two dimensions. Despite the advantages of this method, the process of ranking alternative according to related criteria may need more consideration. Typically, there are contributions in this article. First, a new similarity measure has been introduced followed by a modification applied to TOPSIS analyses. Second, the modified similarity technique was subsequently extended in the fuzzy context to cope with the uncertainty inherently existing in human judgments. A numerical example of the personnel selection was presented to demonstrate the possible application of the proposed method in human resource management. The outcome of applying fuzzy similarity method showed a significant distinction in ranking alternatives compered to TOPSIS method. Therefore, the modification is sound to be a proper solution.
Research Paper
Case studies in industry and services
Seyed Farid Mousavi; Arash Apornak; Mohammadreza Pourhassan
Abstract
Although the importance of supply chain agility considering the necessity of speed of action, response to customers, progressive changes in the market, consumers’ needs, etc. in many industries is clear both scientifically and experimentally, today organizations have found that the ...
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Although the importance of supply chain agility considering the necessity of speed of action, response to customers, progressive changes in the market, consumers’ needs, etc. in many industries is clear both scientifically and experimentally, today organizations have found that the benefit from this cooperation is greater than cases performed without collaboration with relevant organizations. Meanwhile, supply chain management refers to integration of all processes and activities in the supply chain through improving the relations and implementing the organizational processes in order to achieve competitive advantages. On the other hand, uncertainty in the supply chain results in non-optimality of decisions that are made with assumption of certainty. Accordingly, the main aim of this research is to provide a model for supply chain in an agile and flexible state based on uncertainty variables. The method of research has been based on a mathematical model, whose stages of implementation are investigated by breaking down this model step-by-step. For this purpose, in the first stage and after getting familiar with the intended modeling industry, solution and simulation were done. Eventually the results were compared indicating that through reducing the risk-taking (increasing the protection levels), the objective function which was of minimization type worsened. This study also showed that model robustification is very important in order to reduce the risk of decision-making.
SI:RSSCMMA
Supply chain management
Peiman Ghasemi; Hossein hemmaty; Adel Pourghader chobar; Mohamad Reza Heidari; Mahdi Keramati
Abstract
Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to ...
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Today, logistics costs often make up a major part of large organizations’ expenses. These costs can be reduced with optimal design and its implementation in the supply chain. As a result, in present study, a two-objective mathematical location-routing model is presented, where an objective is to minimize the costs and the next is to maximize the reliability in order to deliver the goods timely to customer according to the probable time and time window. The proposed problem has two levels of distribution. The first level, which is called transportation level, points to the distribution of products from a factory to an open distribution center, and the latter is known as routing level, which is related to a part of the problem in which we deliver products from the warehouse to customers. The proposed mathematical model is solved by Epsilon-constraint and NSGA-II approaches in small and medium, and large scales problem, respectively. The present study has provided the following contributions: concurrent locating and routing in the supply chain in accordance with the customer’s time window, probable travel time in the supply chain and customer’s reliability in the supply chain. The assessment metric results indicate the proper performance of our proposed model.
Research Paper
Customer Satisfaction and Loyalty
reza yazdani; Mohammad Javad Taghipourian; Mohammad Mahdi Pourpasha; Seyed Shamseddin Hosseini
Abstract
In the last decade, information and communication technology (ICT) was used as the most effective tool to help businesses gain a competitive advantage by attracting customers. Thus, ICT has significantly contributed to the growth of e-commerce. Internet access allows e-commerce to spread globally and ...
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In the last decade, information and communication technology (ICT) was used as the most effective tool to help businesses gain a competitive advantage by attracting customers. Thus, ICT has significantly contributed to the growth of e-commerce. Internet access allows e-commerce to spread globally and cheaply. However, many organizations did not realize the potential value created by e-commerce. Since the provision of information and branding at the destination necessarily involves the focused attention of all tourism companies in the destination, e-commerce can lead to the development of a new distribution channel in a virtual network and connects the producer with the customer. To this end, the present study analyzed the factors affecting brand strengthening drivers in e-commerce in the Iranian tourism industry. Brand strengthening drivers were ranked using Shannon’s entropy method. The results indicated that advertising and brand communication are the most effective brand strengthening drivers.
Research Paper
Data Envelopment Analysis, DEA
Maryam Arbabi; Zohreh Moghaddas; Alireza Amirteimoori; Mohsen Khunsiavash
Abstract
Sensitivity analysis in optimization problems is important for managers and decision-makers to introduce different strategies. Data envelopment analysis is a method based on mathematical programming to evaluate the efficiency of a set of decision-making units. Due to the importance of sensitivity analysis ...
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Sensitivity analysis in optimization problems is important for managers and decision-makers to introduce different strategies. Data envelopment analysis is a method based on mathematical programming to evaluate the efficiency of a set of decision-making units. Due to the importance of sensitivity analysis in an optimization problem, the development of a data envelopment analysis model called inverse model in data envelopment analysis is presented. The purpose of this model is to analyze the sensitivity of some inputs or outputs to changes in some other inputs or outputs of the unit under evaluation, provided that the amount of efficiency remains constant or improves at the discretion of the manager. In this research, for the first time, we introduce the inverse model in data envelopment analysis with network structure. In fact, we examine the extent to which the input parameters are likely to change based on the presuppositions of the problem, for the output changes that are applied as the manager desires. One of the key points of this research is that to make the modeling more consistent with reality, the leader-follower method was used in estimating the parameters in the network. In addition, the opinions of the system manager and the decision-maker, who have full control over the system under their management, are included in this modeling to estimate the desired values. Another feature of this modeling is the consideration of uncontrollable factors in the inverse model in data envelopment analysis with network structure. Finally, using a numerical example, the results obtained are analyzed based on the proposed model.
Research Paper
Fuzzy optimization
Elham Hosseinzadeh; Javad Tayyebi
Abstract
Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real-life problems. The current paper focuses on the neutrosophic fuzzy multiobjective linear programming problem (NFMOLPP), where the coefficients of the objective functions, ...
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Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real-life problems. The current paper focuses on the neutrosophic fuzzy multiobjective linear programming problem (NFMOLPP), where the coefficients of the objective functions, constraints, and right-hand side parameters are single-valued trapezoidal neutrosophic numbers (NNs). From the viewpoint of complexity of the problem, a ranking function of NNs is proposed to convert the problem into equivalent MOLPPs with crisp parameters. Then suitable membership functions for each objective are formulated using their lowest and highest value. With the aim of linear programming techniques, a compromise optimal solution of NFMOLPP is obtained. The main advantage of the proposed approach is that it obtains a compromise solution by optimizing truth-membership, indeterminacy-membership, and falsity-membership functions, simultaneously. Finally, a transportation problem is introduced as an application to illustrate the utility and practicality of the approach.
Research Paper
Data Envelopment Analysis, DEA
Sima Madadi; Farhad Hosseinzadeh Lotfi; Mehdi Fallah Jellodar; Mohsen Rostamy-Malkhalifeh
Abstract
We developed a DEA-based resource re-allocation model based on environmental DEA technology for organizations with a central decision-making environment. The proposed model considered a weak disposability axiom for undesirable outputs and combined data envelopment analysis (DEA) with multiple-objective ...
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We developed a DEA-based resource re-allocation model based on environmental DEA technology for organizations with a central decision-making environment. The proposed model considered a weak disposability axiom for undesirable outputs and combined data envelopment analysis (DEA) with multiple-objective programing (MOP). The objective was to find the appropriate re-allocation model in order to save energy and reduce environmental pollution, so that the next steps could be taken toward improvement. Given that reducing the inputs and outputs of inefficient units is sometimes not achievable and does not seem logical, for the reduction in the values to be logical and achievable, we divided the decision-making units (DMUs) into different levels of efficient frontier using the context-dependent DEA technique. For this purpose, the model was designed to move the DMUs from the current frontier to the efficient frontier of the previous layer, which has better efficiency conditions, or keep them on their own frontier. In addition, the opinion of the central decision maker regarding the amount of reduction in the inputs and outputs was expressed using Goal Programing (GP) in a way that does not make the model infeasible. By implementing the model in 8 regions of the world, suggestions were made regarding the amounts of energy saving and CO2 pollution reduction based on the conditions determined by the central decision maker aiming improve the efficiency of inefficient units in the next step.
Research Paper
Engineering Modeling
Reza Eslamipoor; Arash Nobari
Abstract
Nowadays, designing a reliable network for blood supply chains by which most blood demands can be supplied is an important problem in the health care systems. In this paper, a multi-objective model is provided to create a sustainable blood supply chain, which contains multiple donors, collection centers, ...
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Nowadays, designing a reliable network for blood supply chains by which most blood demands can be supplied is an important problem in the health care systems. In this paper, a multi-objective model is provided to create a sustainable blood supply chain, which contains multiple donors, collection centers, distribution centers, and hospitals at different echelons. Regarding the potential of a blood shortage occurring, the suggested model considers the supply chain's capacity to meet hospitals' blood demands as dependable and a means of achieving the societal purpose. In addition, limiting the overall cost and environmental effect of designing a supply network and blood transportation are considered economical and environmental objectives. To solve the proposed multi-objective model, an improved ε-constraint approach is first employed to construct a single-objective model. Additionally, an imperialist competitive algorithm is developed to solve the single-objective model. Several test cases are analysed to determine the technique's effectiveness. CPLEX is then used to compare the results.
Research Paper
Game theory
Fatemeh Ghaeminasab; Mohsen Rostamy-Malkhalifeh; farhad hosseinzadeh Lotfi; Mohammad-Hasan Behzadi; Hamidreza Navidi
Abstract
In this paper, while taking into account the cooperative relationships between units, the problem of revenue allocation is considered as a coalitional game. In order for the allocation to be equitable, by relying on the concept of DEA efficiency, a new characteristic function is presented, and then using ...
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In this paper, while taking into account the cooperative relationships between units, the problem of revenue allocation is considered as a coalitional game. In order for the allocation to be equitable, by relying on the concept of DEA efficiency, a new characteristic function is presented, and then using the concept of the Shapley value, which is a well-recognized concept in coalitional game theory, a unique solution is obtained for the revenue allocation problem. And finally, to evaluate the equitability of the performed revenue allocation, the Gini coefficient is utilized. A comparison of the Gini coefficient obtained for our method with those of some existing methods showed that our method is more equitable than the previous ones. This demonstrates how impactful the wise and accurate selection of the characteristic function is in the equitability of the results.
Research Paper
Scheduling
Vahid Bahmani; Mohammad Amin Adibi; Esmaeil Mehdizadeh
Abstract
This paper provides an integrated model for a two-stage assembly flow shop scheduling problem and distribution through vehicle routing in a soft time window. So, a mixed-integer linear programming (MILP) model has been proposed with the objective of minimizing the total cost of distribution, holding ...
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This paper provides an integrated model for a two-stage assembly flow shop scheduling problem and distribution through vehicle routing in a soft time window. So, a mixed-integer linear programming (MILP) model has been proposed with the objective of minimizing the total cost of distribution, holding of products, and penalties of violating delivery time windows. To solve this problem, an improved meta-heuristic algorithm based on whale optimization algorithm (WOA) has been developed. A comparison of the integrated and non-integrated model in a case study of industrial gearboxes production shows that the integrated model compared to the non-integrated model has saved 15.6% and 13.6% in terms of delay time and total costs, respectively. Computational experiments also indicate the efficiency of improved WOA in converging to optimal solution and achieve better solution in comparison to the genetic algorithm (GA).
Research Paper
Industrial Mathematics
Ramin Barati; Sara Fanati Rashidi
Abstract
This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee ...
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This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes Work Itself, Supervision, Coworkers Relationship, Salary and Benefit, Career Opportunities, Job Stress, Perceived Risk, and Job Insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance of dimensions is evaluated by 20 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are salary and benefits. Moreover, the results indicate that the least important dimensions are the Co-workers Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are Work Itself, Job Stress Perceived Risk, and Job Insecurity. In addition, this study’s results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the Below three-star hotels. The results of the study will help businesses in the field of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions.
Research Paper
Scheduling
Bahareh Vaisi; Hiwa Farughi; Sadigh Raissi; Heibatolah Sadeghi
Abstract
In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it ...
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In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it is more complicated than the other cycles, the focus has been on the S_2 cycle as the most frequently employed robot movement cycle. Therefore, a multi-objective mathematical formulation is proposed to minimize cycle time and operational costs. The -constraint method is used to solve small-sized problems. Non-dominated sorting genetic algorithm II (NSGA-II), is used to solve large-sized instances based on a set of randomly generated test problems. The results of several Test problems were compared with those of the GAMS software to evaluate the algorithm's performance. The computational results indicate that the proposed algorithm performs well. Compared to GAMS software, the average results for maximum spread (D) and non-dominated solutions (NDS) are 0.02 and 0.04, respectively.
Research Paper
Performance evaluation and benchmarking
Tri Ngudi Wiyatno; Atty Tri Juniarti; Iman Sudirman
Abstract
The Floor Tiles Industry in accordance with State Regulations is one of the manufacturing industries that can participate in Indonesia into a Developed Industrial Country, supported by the availability of various technologies and product innovations so that domestic floor tiles can be accepted. In the ...
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The Floor Tiles Industry in accordance with State Regulations is one of the manufacturing industries that can participate in Indonesia into a Developed Industrial Country, supported by the availability of various technologies and product innovations so that domestic floor tiles can be accepted. In the face of increasing competition, domestic floor tiles industry trying to improve the quality of the products by implementing a strict standardization system for production processes and products produced by implementing TQM. Based on the components that influence of TQM, variables of leadership, technical competence and organizational culture are closely related to certain factors. A leadership pattern that focuses on goals or targets determined and taken based on scientific thinking by taking into account the various parties involved will improve the quality. Education and training as well as employee involvement by providing controlled independence as well as improving the technical quality.
Research Paper
Decision analysis and methods
Mehdi Soltanifar
Abstract
In this paper, a hybrid method based on a linear programming model for solving Multi-Attribute Decision-Making (MADM) problems by combining two new methods, the COmplex PRoportional Assessment (COPRAS) and the Multi-objective Optimization Ratio Analysis (MOORA) and also using the concept of discrimination ...
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In this paper, a hybrid method based on a linear programming model for solving Multi-Attribute Decision-Making (MADM) problems by combining two new methods, the COmplex PRoportional Assessment (COPRAS) and the Multi-objective Optimization Ratio Analysis (MOORA) and also using the concept of discrimination intensity functions are presented. Further interaction with the Decision Maker (DM) to determine the weights of the attributes and calculate the weights by solving a linear programming problem without determining the predetermined weight are two of the advantages of the new method. In the proposed method, for each alternative, attributes are weighted with optimism for that alternative, and then alternatives are ranked through efficiency intervals. The proposed method is implemented on a real-world problem derived from the subject literature and compared with other MADM methods. The difference in the final results is evident due to the consideration of more details in determining the rankings.
Research Paper
Engineering Optimization
Ayodeji Nathaniel Oyedeji; Ibrahim Iliyasu; James Bitrus Bello; Kazeem Adeniyi Salami; Musa Nicholas Dibal; Danjuma S Yawas
Abstract
This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30-40 wt% and fiber reinforcement ...
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This study considered the consequence of the length and weight composition percentage of Deleb palm fruit fiber on the physio-mechanical characteristics of an epoxy-based composite through the Taguchi grey relational optimization technique. Considering fiber reinforcement of 30-40 wt% and fiber reinforcement length of 1-5mm, the physical and mechanical properties were determined based on standards. The findings demonstrated that the Deleb palm fruit fiber's characteristics tend to differ from those of other types of fiber reinforcement in that they significantly impact the physio-mechanical characteristics of the resulting epoxy-based reinforced Deleb palm fruit fiber composite. The ANOVA result showed that, at a confidence interval of 5%, the effects of the fiber characteristics on the physio-mechanical properties of the composites were particularly notable for tensile strength and a decrease in water absorption.
Research Paper
Quality Control
Forbes Chiromo; Nomupendulo Nokuthula Msibi
Abstract
This single case study examined how key internal audit planning and implementation determinants impacted a South African automotive company's ISO 9001 Quality Management System objectives. The study used a mixed method approach; qualitative data nesting in quantitative data. The purposive sampling technique ...
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This single case study examined how key internal audit planning and implementation determinants impacted a South African automotive company's ISO 9001 Quality Management System objectives. The study used a mixed method approach; qualitative data nesting in quantitative data. The purposive sampling technique was used to collect primary data from managers, internal quality auditors, and auditees. Professional judgment was used to collect secondary data from the 2017 to 2020 audit reports. Descriptive data analysis was conducted on the data collected. The internal audits were conducted beyond departmental boundaries and organizational structures. The audit determinants were; compliance with the ISO 9001 standards, and maintenance of ISO 9001 QMS certification. The process and system internal quality audits were conducted to correct nonconformities before and after external audits. Audit reports from certification bodies also determined the scope of the subsequent internal audit programs for processes and systems. In addition, the internal auditors relied on their judgments and on the technical experts' advice to sample processes, areas, and material to be audited. Management audit review reports also contributed to determining the scope of audit programs. Despite different stakeholders' contributions, the company's internal quality audit programs did not embrace customer focus and continuous improvement. The audit program was a reaction to internal and external stakeholders' complaints. However, the study is fundamental to improving the company's ISO 9001 quality management system performance. It discusses issues that drive the planning and implementation of audit programs. The findings are likely to stimulate similar research in other sectors and on a bigger scale. There are also opportunities to evaluate the determinants related to monitoring, reviewing, and improving audit programs.
Research Paper
Data Envelopment Analysis, DEA
jafar pourmahmoud; Naser Kaheh; farhad hosseinzadeh lotfi
Abstract
In traditional cost-efficiency models, inputs and outputs, as well as input prices were known as constant values for each decision-making unit In our daily applications, however, market entry prices vary at different times. In other words, input prices for decision-making units (DMUs) are time dependent. ...
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In traditional cost-efficiency models, inputs and outputs, as well as input prices were known as constant values for each decision-making unit In our daily applications, however, market entry prices vary at different times. In other words, input prices for decision-making units (DMUs) are time dependent. Traditional methods cannot calculate the cost efficiency of DMUs with time-dependent prices. This paper proposes a new method to calculate the cost efficiency of DMUs in the presence of time-dependent prices. The proposed model is a parametric programming problem model depending on time. In the presented model, the inputs and outputs are functions in terms of time, which is not present in the models introduced by other researchers. New definitions for time-dependent cost efficiency have also been introduced. The cost efficiency of DMUs is measured over a given time and the units are ranked according to the time obtained. Finally, a numerical example has been presented to illustrate the proposed method.
Research Paper
Game theory
Mohammad Shafiekhani; Alireza Rashidi Komijan; Hassan Javanshir
Abstract
The process of transferring money from the treasury to the branches and returning it at specific and limited periods is one of the applications of the Vehicle Routing Problem (VRP). Many parameters affect it but choosing the right route is the most key parameter so that the money delivery process is ...
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The process of transferring money from the treasury to the branches and returning it at specific and limited periods is one of the applications of the Vehicle Routing Problem (VRP). Many parameters affect it but choosing the right route is the most key parameter so that the money delivery process is carried out in a specific period with the least risk. In the present paper, new relationships are defined in the form of three concepts in order to minimize route risk. These concepts are: (i)the vehicle does not travel long routes in the first three movements. (ii)A branch is not served at the same hours on two consecutive days. (iii)An arc should not be repeated on two consecutive days. The proposed model with real information received from Bank Shahr has been performed for all branches in Tehran. Because the vehicle routing problem is an NP-Hard problem, a genetic algorithm was used to solve the problem. Different problems in various production dimensions were solved with GAMS and MATLAB software to show the algorithm solution quality. The results show that the difference between the genetic algorithm and the optimal solution is an average of 1.09% and a maximum of 1.75%.
Research Paper
Risk management
seyed reza seyed nezhad fahim; fatemeh Gholami gelsefid
Abstract
The primary purpose of this research was to understand the importance of supply chain strategies in the field of supply chain risk management, emphasizing the effectiveness and efficiency of agile and lean strategies to create resilience and robustness in the supply chain. Data was collected from 392 ...
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The primary purpose of this research was to understand the importance of supply chain strategies in the field of supply chain risk management, emphasizing the effectiveness and efficiency of agile and lean strategies to create resilience and robustness in the supply chain. Data was collected from 392 supply chain experts working in Iran's automotive industry to test hypotheses through structural equation modeling. The findings of this study show that market orientation (as an external force) has more signicant impact on the development of agile strategy than lean strategy. In contrast, the quality management system (as an internal force) is highly correlated with the development of lean supply chain strategies. Moreover, agile and lean strategies also have a signicant impact on a resilient and robust supply chain. The proposed model helps organizations understand and create an ideal supply chain by implementing the right combination of both agile and lean supply chain strategies, which in turn helps to create a resilient and robust supply chain. Therefore, the findings of this study help policymakers to improve supply chain strategies by incorporating new management practices. This is original research that has various valuable insights for academic researchers and also supply chain strategy professionals as it reveals empirical evidence of the past vital concepts.
Research Paper
Case studies in industry and services
Robert S Keyser; Parisa Pooyan
Abstract
In a Lean production environment, reduced setup times can lead to many benefits, including reduced lead times. Previous research has primarily relied on the SMED methodology and mathematical modeling to reduce setup times at machine centers – and both are very useful techniques. We use the Soft ...
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In a Lean production environment, reduced setup times can lead to many benefits, including reduced lead times. Previous research has primarily relied on the SMED methodology and mathematical modeling to reduce setup times at machine centers – and both are very useful techniques. We use the Soft Systems Methodology, combined with the Seven Tools of Quality, to provide a structured, illustrative means for diagnosing production and quality issues. A baseline average setup time was established by which future setup times would be compared. The intervention included brainstorming sessions between management and the converting center work crew that disclosed many reasons for increased setup times, some of which were under management’s control. Our findings resulted in a 24% reduction in average setup times and a 62% reduction in the moving range at a bottleneck machine center in the corrugated box industry.
Research Paper
Forecasting, production planning, and control
Obojobo Obukeajeta Donatus; Chima Uzorh
Abstract
Economic or local disruptions that affect organizations' production activities often result in unexpected losses. An excellent example is the recent COVID-19 pandemic disruption which affected many economies globally. This study presents a deterministic model and uses simple regression analysis to estimate ...
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Economic or local disruptions that affect organizations' production activities often result in unexpected losses. An excellent example is the recent COVID-19 pandemic disruption which affected many economies globally. This study presents a deterministic model and uses simple regression analysis to estimate the average condition for production losses. Its corresponding components' input resources impact the overall estimates for selected organizations in Nigeria. It is anticipated that variability in economic activities is always accompanied by unconventional stock returns whose behaviour indicates prevailing economic trends. Here we have looked at two organizations in the manufacturing sector as a case study; Nigerian Breweries and Nestle Nigeria, whose stock prices[X] upon analysis reveal that at[X]≤N30 and [X]≤N821 are estimated conditions for zero net profit for both organizations respectively. Therefore, for Nigerian Breweries, during the four quarters of the 2020 fiscal year, the following were assessed production losses,3.47 billion naira(Q1), 4.17 billion naira(Q2), 3.72 billion naira(Q3) and 0.68 billion naira(Q4) with a total of 12.04 billion naira annual estimated losses; with COGS,OPEX and SAEX having 39.6%,44.5% and 15.9% impact on the estimates. Nestle Nigeria records estimated production losses of 5.8 billion naira (Q1), 6.4 billion naira(Q2),4.2 billion naira(Q3), and -0.8 billion naira(Q4) (gain), resulting in a total 15.6 billion naira annual estimated loss; and COGS,OPEX, and SAEX having 45.9%, 48.2% and 5.9% impact on the estimates respectively. This implies, Selling and Advertising Expenses (SAEX) had the most negligible percentage impact on overall estimated production losses for both organizations compared to Costs of Goods Sold (COGS) and Operating Expenses (OPEX).This study, therefore, reiterates the position of other economic reports describing the adverse effects of the pandemic in Nigeria; while also serving as an investment analysis guide to potential investors..
Research Paper
Supply chain management
Javid Ghahremani-Nahr; Abdolsalaam Ghaderi; Ramez Kian
Abstract
This article deals with the modeling of the food bank (FB) network in the conditions of uncertainty in the demand of charities and the capacity of donating food. The importance of creating a FB network, along with providing quality food, led to consider the two objective functions of minimizing the costs ...
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This article deals with the modeling of the food bank (FB) network in the conditions of uncertainty in the demand of charities and the capacity of donating food. The importance of creating a FB network, along with providing quality food, led to consider the two objective functions of minimizing the costs of the total FB network and maximizing the minimum freshness of the food basket. The simultaneous optimization of the above two objective functions is aimed at making correct routing-inventory and allocation decisions. In this paper, food items in food baskets with high shelf-life and low shelf-life are considered. The results of solving the sample problems by combining the operators of two Genetic Algorithm (GA) and Salp Swarm Algorithm (SSA) showed that with the increase in the freshness of the food baskets, the costs of the FB network have increased. Also, the sensitivity analysis showed that the increase in uncertainty in the network leads to an increase in the cost of FB network and a decrease in the freshness of the food basket. The comparison of the results between the algorithms also showed that the efficiency of HGSSA is much higher than GA and SSA and the problem solving time by these methods is extremely lower. The use of HGSSA has increased the rate of achieving effective solutions by 14.06%.
Research Paper
Operations Research
hajar shirneshan; Ahmad Sadegheih; H. Hosseini-Nasab; mohammd mehdi lotfi
Abstract
Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. ...
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Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. Given the uncertainty in patients' demands, it is an important issue as to how to assign care providers to different shifts. One area facing this uncertainty is the provision of services to cancer patients. A stochastic programming model is developed to account for patient demand uncertainty by considering different skills and contracts for care providers in this study. In the first step, care providers are assigned to work shifts, then, in the second step, the required overtime hours are determined. The sample average approximation method is presented to determine an optimal schedule by minimizing care providers' regular and overtime costs with different contracts and skills. Then, the appropriate sample size is 100, which is determined based on the Monte Carlo and Latin Hypercube methods. In the following, the lower and upper bounds of the optimal solution are calculated. As the numerical results of the study show, the convergence of the lower and upper bounds of the optimal solution is obtained from the Latin Hypercube method. The best solution is equal to 189247.3 dollars and is achieved with a difference of 0.143% between the upper bound and lower bounds of the optimal solution. The Monte Carlo simulation method is used to validate the care provider program in the next stage. As shown, in the worst case, the value of the objective function is equal to 197480 dollars.
Research Paper
Engineering Computations
Ali Mahmoudloo
Abstract
We use the charge extraction by linearly increasing voltage (CELIV) technique to calculate the drift velocity and mobility of holes in organic semiconducting polymers . The essence of this technique to measure the charge carrier mobility is very simple. The charge carrier mobility is defined as carrier ...
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We use the charge extraction by linearly increasing voltage (CELIV) technique to calculate the drift velocity and mobility of holes in organic semiconducting polymers . The essence of this technique to measure the charge carrier mobility is very simple. The charge carrier mobility is defined as carrier drift velocity v in a given electric field E. It is a complimentary technique in the sense that it allows to study materials when other techniques such as Time-of-Flight are inapplicable. Typically, Photo-CELIV is used to measure the charge carrier mobility in organic semiconductors since they are large bandgap (2 eV or so) and not much thermally generated carriers are present for extraction in the dark. The effect of recombination mechanism on the carrier mobility in the organic layer is investigated.
