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
Data Envelopment Analysis, DEA
Rita de Fátima Muniz; Wagner Bandeira Andriola; Sheila Maria Muniz; Antônio Clécio Fontelles Thomaz
Abstract
The present article is an excerpt from a research published in the Journal Revista Ensaio: Avaliação e Políticas Públicas em Educação (2021). The present study adopted the Data Envelopment Analysis (DEA) methodology, to identify the weightiest factors that are ...
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The present article is an excerpt from a research published in the Journal Revista Ensaio: Avaliação e Políticas Públicas em Educação (2021). The present study adopted the Data Envelopment Analysis (DEA) methodology, to identify the weightiest factors that are associated with student performance on large-scale assessments, amongst them, the permanent assessment system for basic education (spaece) test. The DEA Slacks-Based-Measure (SBM) model was used to estimate the relative efficiency of school units in the City of Sobral (CE), one of the most prominent Brazilian counties in the educational scenario. It was evident that the presence of libraries, computer labs, sports courts and rooms for special care in school units constitutes a significant factor associated with the high performance of students, impacting, therefore, on school efficiency.
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
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
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
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
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
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
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.
Research Paper
Corporate Finance
Maryam Mohammad Ganji Nik; Gholamhosein Golarzi; Mohsen Shafiei Nikabadi; Mohammadjavad Fadaiei Eslam
Abstract
In this study, we explain the possible future scenarios of factors affecting stock price fluctuations in the Tehran Stock Exchange, with Respect to 2026 Perspective. This research is applied, cross-sectional, and qualitative, and is implemented as a descriptive survey using the scenario planning Approach. ...
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In this study, we explain the possible future scenarios of factors affecting stock price fluctuations in the Tehran Stock Exchange, with Respect to 2026 Perspective. This research is applied, cross-sectional, and qualitative, and is implemented as a descriptive survey using the scenario planning Approach. The statistical population is a collection of financial experts; We selected 15 of them as a sample using the judgmental/purposive and network (snowball) sampling methods. In the first step, we identified the key uncertainties of the factors affecting stock price fluctuations using the Fuzzy Delphi method, then by identifying the possible modes of each of the key uncertainties, three compatible scenarios were determined by Scenario Wizard software, and finally, the experts suggested strategies for these scenarios.
Research Paper
Data Envelopment Analysis, DEA
Shokouh Shahbeyk; Shokoofe Banihashemi
Abstract
One of the most important aspects of credit risk management is determining the capital requirement to cover the credit risk in a bank loan portfolio. This paper discusses the credit risk of a loan portfolio can be obtained by the stochastic recovery rate based on two approaches: beta distribution and ...
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One of the most important aspects of credit risk management is determining the capital requirement to cover the credit risk in a bank loan portfolio. This paper discusses the credit risk of a loan portfolio can be obtained by the stochastic recovery rate based on two approaches: beta distribution and short interest rates. The capital required to cover the credit risk is achieved through the Vasicek model. Also, the Black-Scholes Merton model for european call option is utilized to quantify the probability of default. Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) are utilized as measures of risk to evaluate the level of risk obtained by the worst-case Probability Of Default (PD) a stochastic recovery rate is used for calculating VaR which relates to the underlying intensity default. In addition, the intensity default process is assumed to be linear in the short-term interest rate, which is driven by a CIR process. By considering the relevant characteristics with Data Envelopment Analysis (DEA) method, the loan portfolio performance is evaluated. This study proposes the losses which are driven by the stochastic recovery rate and default probability. The empirical investigation measures the PD of eighth stocks from different industries of the Iran stock exchange market by using the Black-Sholes-Merton model.
Research Paper
Performance evaluation and benchmarking
SUPRIYATI SUPRIYATI
Abstract
Company is an organization that provides or produces products/services. Various types of companies and the complexity of the process make the company must be able to continue to grow and compete with competitors. To win the competition, companies must have a strategy to improve performance. TPM is part ...
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Company is an organization that provides or produces products/services. Various types of companies and the complexity of the process make the company must be able to continue to grow and compete with competitors. To win the competition, companies must have a strategy to improve performance. TPM is part of the strategy implemented in the company. In Indonesia, not all companies apply TPM, automotive component painting companies apply and measure performance through PQCDSM as a whole. The result of TPM implementation is an increase in production performance which has an impact on reducing quality costs, increasing production, increasing the effectiveness of equipment use because the total of damaged equipment is less. TPM implementation through OEE production performance/engine efficiency increased by 68.7%
Research Paper
Forecasting, production planning, and control
Samrad Jafarian-Namin; Davood Shishebori; Alireza Goli
Abstract
The temperature has been a highly discussed issue in climate-changing. Predicting it plays an essential role in human affairs and lives. It is a challenging task to provide an accurate prediction of air temperature because of its complex and chaotic nature. This issue has drawn attention to utilizing ...
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The temperature has been a highly discussed issue in climate-changing. Predicting it plays an essential role in human affairs and lives. It is a challenging task to provide an accurate prediction of air temperature because of its complex and chaotic nature. This issue has drawn attention to utilizing the advances in modeling capabilities. ARIMA is a popular model for describing the underlying stochastic structure of available data. Artificial neural networks (ANNs) can also be appropriate alternatives. In the literature, forecasting the temperature of Tehran using both techniques has not been presented so far. Therefore, this article focuses on modeling air temperatures in the Tehran metropolis and then forecasting for twelve months by comparing ANN with ARIMA. Particle swarm optimization (PSO) can help deal with complex problems. However, its potential for improving the performance of forecasting methods has been neglected in the literature. Thus, improving the accuracy of ANN using PSO is investigated as well. After evaluations, applying the seasonal ARIMA model is recommended. Moreover, the improved ANN by PSO outperforms the pure ANN in predicting air temperature
Research Paper
Data Envelopment Analysis, DEA
Leila Khoshandam; Maryam Nematizadeh
Abstract
The inverse data envelopment analysis (DEA) problem has been one of the most important issues in the last decade. The inverse DEA permits the chief manager to increase (or decrease) outputs (or inputs) of decision-making units (DMUs) in such a way that the level of the relative efficiency of the under–observed ...
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The inverse data envelopment analysis (DEA) problem has been one of the most important issues in the last decade. The inverse DEA permits the chief manager to increase (or decrease) outputs (or inputs) of decision-making units (DMUs) in such a way that the level of the relative efficiency of the under–observed DMU is preserved. Due to the importance of network-structured production systems in real life, the main purpose of the present research is to provide an inverse DEA model for a two-stage network-structured production system in the presence of undesirable factors. The weak disposability assumption is used to handle undesirable outputs in the proposed model. The focus of the proposed model is on estimating the amount of change in one or more indicators of one stage of the process by changing the indicators of another stage to preserve the level of efficiency. The most important advantage of the proposed procedure is that it can increase the level of outputs and simultaneously reduce the level of inputs. To demonstrate its practical use, the model is applied to a real-life example in poultry farming.
Research Paper
Case studies in industry and services
MOJISOLA ADERENIKE BOLARINWA; Emmanuel Chukwuwuikem Ofiebor
Abstract
The quality-of-service delivery in any organization needs to be at its best, otherwise, there would be losses in that organization. The health industry, particularly hospitals and specifically emergency departments in hospitals are not excluded. If anything, they play such vital roles that its evaluation ...
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The quality-of-service delivery in any organization needs to be at its best, otherwise, there would be losses in that organization. The health industry, particularly hospitals and specifically emergency departments in hospitals are not excluded. If anything, they play such vital roles that its evaluation needs to be carried out as regularly as possible. Several methods have been deployed in order to evaluate service quality. Two of these methods; the Taguchi approach and the SERVAQUAL approach have been utilized and compared in this research. The Taguchi approach, through the application of mini-tab software, showed that the role of the Nurses in the emergency department appeared to be the most vital. The SERVAQUAL approach revealed that patients perceived empathy from the workers as the highest quality displayed by staff in the department. It can be concluded that these two approaches gave similar results, as Nurses are trained particularly to have a great deal of empathy.Keywords: Emergency department, Health, Patients, Service Quality, Taguchi.
Research Paper
Industrial Mathematics
Mohammad Shafiekhani; Alireza Rashidi Komijan; Hassan Javanshir
Abstract
In this paper, a new type of vehicle routing problem in the valuable commodity transportation industry is modeled considering the route risk constraint. The proposed model has two objective functions for risk minimization. In the first objective function, three concepts are presented, which are: 1) the ...
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In this paper, a new type of vehicle routing problem in the valuable commodity transportation industry is modeled considering the route risk constraint. The proposed model has two objective functions for risk minimization. In the first objective function, three concepts are presented, which are: 1) the vehicle does not travel long distances in the first three moves because it carries more money, 2) to serve the same branch on two consecutive days, at the same time 3) The bow should not be repeated in two consecutive days. This reduces the possibility of determining a fixed pattern for the service and increases the security of the service. In the second objective function, risk is a function of the amount of money, the probability of theft and the probability of its success. To solve the proposed model, two different meta-heuristic algorithms including genetic algorithm and ant colony optimization algorithm have been used. In computational testing, the best parameter settings are determined for each component and the resulting configurations are compared in the best possible settings. The validity of the answers of the algorithms has been investigated by generating different problems in various dimensions and using the real information of Shahr Bank. The results show that the genetic algorithm provides better results compared to the ant colony algorithm with an average of 0.93% and a maximum of 1.87% difference with the optimal solution.
Research Paper
Computational modelling
Eshetu Dadi Gurmu; Mengesha Dibru Firdawoke; Mekash Ayalew Mohammed
Abstract
In this paper, a nonlinear mathematical model of COVID-19 was formulated. We proposed a SEIQR model using a system of ordinary differential equations. COVID-19 free equilibrium and endemic equilibrium points of the model are obtained. A basic reproduction number of the model is investigated by the next-generation ...
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In this paper, a nonlinear mathematical model of COVID-19 was formulated. We proposed a SEIQR model using a system of ordinary differential equations. COVID-19 free equilibrium and endemic equilibrium points of the model are obtained. A basic reproduction number of the model is investigated by the next-generation matrix. The stability analysis of the model equilibrium points was investigated using basic reproduction numbers. The results show that the disease-free equilibrium of the COVID-19 model is stable if the basic reproduction number is less than unity and unstable if the basic reproduction number is greater than unity. Sensitivity analysis was rigorously analyzed. Finally, numerical simulations are presented to illustrate the results.
Research Paper
Case studies in industry and services
Kh. Ghaziyani; farhad hosseinzadeh Lotfi; Sohrab Kordrostami; alireza amirteimoori
Abstract
Today, one of the main problems in many organizations such as banks with many branches, is that the method of evaluating them is not correct. The traditional techniques used to evaluate performance are often single-level and do not provide the manager with enough information to identify the inefficiency ...
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Today, one of the main problems in many organizations such as banks with many branches, is that the method of evaluating them is not correct. The traditional techniques used to evaluate performance are often single-level and do not provide the manager with enough information to identify the inefficiency causes of inefficient units. In contrast, Bi-level Data Envelopment Analysis (DEA) models solve the problem of ignoring internal relationships. In this paper, first, the factors that had a higher rank were selected as input and output factors with the help of bank experts and the AHP method. Then, the performance of 30 branches of the Central Bank of Iran was evaluated using the leader-follower method and generalizing Russell's non-radial method. In this paper, the intermediate data is desirable and undesirable. The results showed that the proposed model does not have the problems of traditional models and provides a more realistic assessment of the efficiency of bank branches.
Research Paper
Supply chain management
Fatemeh Kangi; Seyed Hamid Reza Pasandideh; Esmaeil Mehdizadeh; Hamed Soleimani
Abstract
In recent years, the expansion of social responsibility concept, increased environmental considerations, economic incentives and governmental pressure on manufacturers for waste management have caused organizations to focus attention on the development of closed-loop supply chains (CLSC) and reverse ...
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In recent years, the expansion of social responsibility concept, increased environmental considerations, economic incentives and governmental pressure on manufacturers for waste management have caused organizations to focus attention on the development of closed-loop supply chains (CLSC) and reverse logistics (RL) processes. The adoption of these approaches, will enable organizations to simultaneously meet economic, social and environmental goals and consider the manufacturing cycle from supply and production to reuse of products. Hence, this study deals with an optimization model within the framework of a multi-echelon, multi-product and multi-period CLSC with hybrid facilities where cross-docking strategy and vehicle routing with soft time windows have been included in the model. In the problem defined as a MILP model, decisions are made simultaneously at three levels of strategic, tactical and operational. Furthermore, to tackle the NP-hard problem and achieve near-to-optimal results in reasonable time, two meta-heuristic algorithms, NRGA and MOPSO are developed and the algorithms’ parameters are tuned using the Taguchi method. Finally, the computational results are examined by the performance measures and statistical analysis and the sensitivity analysis is performed regarding the impacts of demand and rate of returned product on the objective functions’ values.
Research Paper
Supply chain management
Pooria Malekinejad; Seyed Haidar mirfakhradini; Ali Morovati sharifabadi; Seyed Mahmood Zanjirchi
Abstract
The increasing use of electronic goods worldwide has led to a significant increase in the amount of waste generated from their consumption, resulting in a major environmental concern. In response, this study aims to provide a systemic framework for reducing electronic waste by considering the benefits ...
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The increasing use of electronic goods worldwide has led to a significant increase in the amount of waste generated from their consumption, resulting in a major environmental concern. In response, this study aims to provide a systemic framework for reducing electronic waste by considering the benefits of a closed-loop sustainable supply chain. To achieve this goal, a systematic literature review was conducted to identify influential factors related to the green supply chain. Based on the identified factors in this section regarding electronic waste, a systematic framework was devised for the technology park companies' chain in Yazd. Accordingly, utilizing fuzzy cognitive mapping technique based on the current state, a systemic structure was formed. The statistical population of this study consisted of industry experts in e-waste in Iran. The initial criterion for identifying these individuals was having at least one international research publication or a minimum of 10 years of work experience in this field. These individuals were selected using the snowball sampling method. After completing the snowball sampling process, 72 experts were selected. Based on this framework, forward and backward scenarios were created to offer practical solutions for addressing the problem of electronic waste in Iran. The results of this study suggest that instead of discarding a significant portion of electronic waste, efforts should be focused on cost reduction through better recycling processes. By implementing a closed-loop sustainable supply chain, businesses can recover valuable resources from electronic waste, reduce their carbon footprint, and ultimately contribute to creating a more sustainable future.
Research Paper
Fuzzy sets and systems
Abouzar Sheikhi; M. J. Ebadi
Abstract
Linear fractional programming (LFP) is a powerful mathematical tool for solving optimization problems with a ratio of linear functions as the objective function. In real-world applications, the coefficients of the objective function may be uncertain or imprecise, leading to the need for interval coefficients. ...
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Linear fractional programming (LFP) is a powerful mathematical tool for solving optimization problems with a ratio of linear functions as the objective function. In real-world applications, the coefficients of the objective function may be uncertain or imprecise, leading to the need for interval coefficients. This paper presents a comprehensive study on solving linear interval fractional transportation problems with interval objective function (ILFTP) which means that the coefficients of the variables in the objective function are uncertain and lie within a given interval.We propose a novel approach that combines interval analysis and optimization techniques to handle the uncertainty in the coefficients, ensuring robust and reliable solutions.The variable transformation method used in this study is a novel approach to solving this kind of problems. By reducing the problem to a nonlinear programming problem and then transforming it into a linear programming problem, the proposed method simplifies the solution process and improves the accuracy of the results. The effectiveness of the proposed method is demonstrated through various numerical examples and comparisons with existing methods. The outcomes demonstrate that the suggested approach is capable of precisely resolving ILFTPs. Overall, the proposed method provides a valuable contribution to the field of linear fractional transportation problems. It offers a practical and efficient solution to a challenging problem and has the potential to be applied in various real-world scenarios.
Research Paper
Computational Intelligence
ramin mousa; Mohammad Ali Dadgostarnia; Amir Olfati Malamiri; Elham Behnam; Shahram Miri Kelaniki
Abstract
Sentiment Analysis (SA) is the computational analysis of ideas, feelings and opinions using natural language processing techniques, computational methods and text analysis to extract polarity (positive, negative or neutral) from unstructured documents or textual comments. Multi-domain SA is based on ...
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Sentiment Analysis (SA) is the computational analysis of ideas, feelings and opinions using natural language processing techniques, computational methods and text analysis to extract polarity (positive, negative or neutral) from unstructured documents or textual comments. Multi-domain SA is based on a labelled dataset, which reduces the dependence on large amounts of domain-specific data and addresses data scarcity issues by leveraging existing data from other domains. This paper presents a novel deep learning-based approach for Persian multi-domain SA analysis. The proposed Bi-IndRNNCapsule technique combines bidirectional IndRNN and CapsuleNet, which use Bi-GRU to extract features for CapsuleNet. In IndRNN, recurrent layer neurons operate independently, with simple RNN computing the hidden state h via element-wise vector multiplication u * state, indicating that each neuron has a solitary recurrent weight linking it to the most recent hidden state. We evaluated the proposed approach on the Digikala dataset and found it to provide acceptable accuracy compared to existing techniques.
Review Paper
Human factors, ergonomics, and safety
Md Sumon Rahman; Jiro Sakamoto
Abstract
Construction trades are considered to be at high risk for work-related musculoskeletal disorders (WRMSDs) due to their nature. Previous reviews have addressed various risk factors for developing WRMSDs among construction workers. In contrast, the results appear insufficient because proper evidence was ...
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Construction trades are considered to be at high risk for work-related musculoskeletal disorders (WRMSDs) due to their nature. Previous reviews have addressed various risk factors for developing WRMSDs among construction workers. In contrast, the results appear insufficient because proper evidence was not reported. Therefore, the purpose of this current review was to summarize the occurrence rates of WRMSDs and quantify the relationships between various risk factors and WRMSDs among construction workers. Literature searches were conducted through the following electronic databases from 2000 to 2022: Science Direct, PubMed, Web of Science, Google Scholar, Research Gate, and Medline. Selected articles were classified as strong, moderate, limited, and no effect, respectively, based on their association with WRMSDs. From the selected 66 articles, the highest occurrence rates of WRMSDs were found in construction workers (ranging from 33% to 89%). There were various significant risk factors for developing WRMSDs in construction workers, including age, working experiences, awkward working postures, vibration, repetitive body movement, manual material handling, biomechanical stress, and physical fatigue. Although most of the study was conducted through a cross-sectional survey to find out the relationships between risk factors and WRMSDs in construction workers. To determine the insights on risk factors and WRMSDs among construction workers, experimental, longitudinal, and real-time task-based studies can be conducted. This study may be helpful to improve awareness about risk factors for developing WRMSDs among construction workers.
Research Paper
Innovation, knowledge management, and organizational learning
mojtaba mohamadjkhani; Reza Radfar; nazanin Pilevarisalmasi; mohamadali afsharkazemi
Abstract
In the past, companies relied only on internal intellectual resources and tried to develop and commercialize ideas within the organization. The open innovation approach leads companies to make more use of external technologies in their activities and allows other companies to use their innovations. Open ...
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In the past, companies relied only on internal intellectual resources and tried to develop and commercialize ideas within the organization. The open innovation approach leads companies to make more use of external technologies in their activities and allows other companies to use their innovations. Open innovation methods have a high diversity, but each economic enterprise should use one or more methods compatible with the company's situation according to its conditions. In the current research, a network-based fuzzy inference system has been used as one of the methods of artificial intelligence and MATLAB software to choose the appropriate method of open innovation in the automotive industry. For this purpose, 2 inputs under the title of company's technical knowledge level and the complexity of parts technology and 9 possible modes for the output including all kinds of open innovation methods are considered in the fuzzy inference system so that by using the existing rules, a technique suitable to the company's conditions can be extracted. In this research, 50% of the data were considered training data for model design, and 50% of the data were considered test data for model evaluation. The designed model selected open innovation methods with 90% accuracy. Therefore, the presented model is a suitable tool for choosing the open innovation method for the automotive industry.
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