Data Envelopment Analysis, DEA
Shokouh Shahbeyk; Shokoofe Banihashemi
Abstract
One of the most critical aspects of credit risk management is determining the capital requirement to cover the credit risk in a bank loan portfolio. This paper discusses how the credit risk of a loan portfolio can be obtained by the stochastic recovery rate based on two approaches: beta distribution ...
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One of the most critical aspects of credit risk management is determining the capital requirement to cover the credit risk in a bank loan portfolio. This paper discusses how 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 the European call option is utilized to quantify the Probability of Default (PD). Value at Risk (VaR) and Conditional Value at Risk (CVaR) are used as measures of risk to evaluate the level of risk obtained by the worst-case PD. A stochastic recovery rate calculates VaR related to the underlying intensity default. In addition, the intensity default process is assumed to be linear in the short-term interest rate, driven by a CIR process. The loan portfolio performance is evaluated by considering the relevant characteristics with the Data Envelopment Analysis (DEA) method. This study proposes the losses driven by the stochastic recovery rate and default probability. The empirical investigation uses the Black-Sholes-Merton model to measure the PD of eighth stocks from different industries of the Iran stock exchange market.
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.
Computational modelling
Samaneh Akbarpour; Abdollah Shidfar; Hashem Saberi Najafi
Abstract
In this article, a mathematical model of the inverse problem is considered. Based on 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. Based on 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 accurate solution to this problem, the operational matrix of shifted Chebyshev polynomials is investigated in conjunction with tau scheme. To demonstrate the validity and applicability of the developed scheme, numerical example is presented.
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.
Decision analysis and methods
Parviz Banafshi; Soleyman Iranzadeh; Houshang Taghizadeh
Abstract
The business process turbulence and the increasing competition among business firms have made the environment around organizations much different than before. Knowing the future business paths and moving in their direction in a way that benefits the organization indicates the necessity of marketing research ...
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The business process turbulence and the increasing competition among business firms have made the environment around organizations much different than before. Knowing the future business paths and moving in their direction in a way that benefits the organization indicates the necessity of marketing research and concepts such as market-centric. This study aims to evaluate the impact of market-centric on organizational performance by emphasizing the mediating role of organizational innovation in the value chain and provide a model for it. This research is a descriptive-survey study. Confirmatory Factor Analysis (CFA) technique has been used to evaluate the significance of regression weight (factor loading) of different constructs of the questionnaire in predicting the relevant items. LISREL statistical analysis software has been used to test the research hypotheses and analysis of structural equations. The statistical population of the study is all managers and employees working in the value chain of poultry industry in Kurdistan province, which 205 samples have been selected based on Cochran's formula. The results of data analysis indicate that the relationship between customer-centric and inter-task coordination with organizational innovation as well as the relationship between pivotal competition and organizational innovation with the financial performance of the organization was confirmed. There is no significant relationship between pivotal competition and organizational innovation, as well as between customer-centric and inter-task coordination with financial performance of the organization. Finally, some suggestions have been made to improve the performance of the poultry industry.
Risk management
Mohammad Reza Alijanzadeh; Seyed Ahmad Shayannia; Mohammad Mehdi Movahedi
Abstract
A system's approach depends on the low malfunction of the equipment and processes of that system, and maintenance plays an essential role in achieving this goal. In addition, over time, the equipment quality decreases, and a quality transfer from controlled to uncontrolled mode may occur, characterized ...
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A system's approach depends on the low malfunction of the equipment and processes of that system, and maintenance plays an essential role in achieving this goal. In addition, over time, the equipment quality decreases, and a quality transfer from controlled to uncontrolled mode may occur, characterized by an increase in the rate of return of the product and the tendency to fail. One of the methods that researchers have widely used in analyzing the risk of net operations is the analysis of the effect and failure modes to identify critical failure modes and focus planning and net resources on them. In analyzing the effect and failure modes, one of the essential steps is prioritizing the equipment to determine the critical equipment, as well as determining the fundamental failure modes and prioritizing them to plan the net operation purposefully. This paper aims to dynamically rank equipment in intuitionistic fuzzy environments with interval values to identify and prioritize critical equipment and 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 piece of equipment according to the conditions of each piece of equipment in the indicators of failure probability, failure consequence, and lack of fault detection power. Therefore, dynamic ranking is provided for the equipment. In this research, for dynamic prioritization of equipment, the method of analysis of the ratio of intuitionistic 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, i.e., 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 equipment's weight and dynamic rating and provides more logical rating results.
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 benefit ...
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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.
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 (MO) (as an external force) has more signicant impact on the development of Agile Strategy (AS) than Lean Strategy (LS). In contrast, the Quality Management (QM) 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 (RB). 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 RB. 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.
Ali Fallahi Rahmat Abadi; 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 CF 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.
Heuristics and Metaheuristics Algorithms
Mehdi Khadem; Abbas Toloie Eshlaghy; Kiamars Fathi
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.
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 (QMS) objectives. The study used a mixed method approach; qualitative data nesting in quantitative data. The purposive sampling ...
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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 (QMS) 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 QMS 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.
Thermal Comfort
Ubeidulla F. Al-Qawabeha
Abstract
AISI H13 tool steel is applied widely to produce many kinds of hot work dies, such as forging dies, extrusion dies, die-casting dies and so on. The successful employment of metal in engineering application relies on the ability of the metal to meet design and services requirements and to be fabricated ...
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AISI H13 tool steel is applied widely to produce many kinds of hot work dies, such as forging dies, extrusion dies, die-casting dies and so on. The successful employment of metal in engineering application relies on the ability of the metal to meet design and services requirements and to be fabricated to the proper dimensions. The capability of metal to meet these requirements is determined by mechanical and physical properties of the metal. Burnishing processes is considered as a surface plastic deformation method, which used to improve surface texture (micro hardness, average surface roughness, and maximum surface roughness). This work present the effect of isothermal annealing temperature and roller burnishing process on the surface properties of H13 alloy steel .This steel was annealed at a different temperatures to get different types of pearlite with different grains and grain size. After that, the steel was burnished with different forces, feeds, and burnishing speeds. The effect of annealing temperatures and roller burnishing on the hardness, micro hardness, average surface roughness and microstructure and metallographic analysis have been investigated. The results showed that roller burnishing could increase the surface hardness under the selected specified conditions depending on the isothermal annealing temperatures by 104%, 45% and 90% for the work parts with 3000C, 500 0C and 6200C annealing temperatures respectively. In addition, roller burnishing significantly improves the smoothness of the steel surfaces. The average roughness obtained was ranged from 0.11μm to 0.17μm. In this paper, the microstructure analysis, micrograph of the isothermal annealed H13 alloy steel have been given. It has been shown that depending on the isothermal annealing temperature there are different types of grains and grain size of treated steel in pearlite phase.
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 key parameter so that the money delivery process is carried ...
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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 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: 1) the vehicle does not travel long routes in the first three movements, 2) a branch is not served at the same hours on two consecutive days, and 3) 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 VRP is an NP-Hard problem, a genetic algorithm was used to solve the problem. Different issues 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%.
Performance evaluation and benchmarking
Supriyati Supriyati; Tri Ngudi Wiyatno
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%.
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.
Transportation
Azra Ghobadi; Reza Tavakkoli Moghadam; Mohammad Fallah; Hamed Kazemipoor
Abstract
The use of an Electric Vehicle (EV), particularly in different operations of goods distribution is a solution for salvaging the crowded cities of the world from air and noise pollutions as well as Green House Gas (GHG) emission. This paper presents a Multi-Depot Electric Vehicle Routing Problem (MD-EVRP) ...
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The use of an Electric Vehicle (EV), particularly in different operations of goods distribution is a solution for salvaging the crowded cities of the world from air and noise pollutions as well as Green House Gas (GHG) emission. This paper presents a Multi-Depot Electric Vehicle Routing Problem (MD-EVRP) with recharging stations by considering the expected penalty of fuzzy time windows in pickup/delivery. Since the MD-EVRP with Fuzzy Time Windows and Pickup/Delivery (MD-EVRP-FTW-PD) constraints is an NP-hard problem, three meta-heuristics (i.e., Simulated Annealing (SA), Variable Neighborhood Search (VNS) and a hybrid of SA and VNS (VNS-SA)) are used to solve such a hard problem. The parameters of these algorithms are measured by the Taguchi experimental design method. The proposed hybrid VNS-SA algorithm is more efficient in comparison with other algorithms.
Decision analysis and methods
Adel Azami; Hanif Kazerooni; Hossein Mohammadkhani Ghiasvand
Abstract
The production and service functions in the innovation system emphasize producing new products. As any innovation system’s final output must ultimately produce new products and deliver new services, the considered function is essential in the innovation system. This study seeks to extract the challenges ...
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The production and service functions in the innovation system emphasize producing new products. As any innovation system’s final output must ultimately produce new products and deliver new services, the considered function is essential in the innovation system. This study seeks to extract the challenges and give solutions to improve the production and deliver services in the innovation system. Producing and delivering services does not occur in a vacuum and should occur in a context called the Supply Chain (SC). In this paper, qualified experts were interviewed to discover the challenges and solutions to improve production. Fifteen elite researchers in the innovation field then discussed the results in focus sessions and refined practical solutions after an in-depth review of the extracted information. The role of responsible institutions was determined, and the necessary indicators were extracted to evaluate the factors of innovative production after providing the required infrastructure to achieve production promotion. One of the Fuzzy Multi-Attribute Decision Making (FMADM) techniques is also used to prioritize the discovered solutions based on the importance of influencing the producing promotion. Finally, a model is presented for improving the production and service functions in the innovation system. The results showed the main solution is to collaborate and create efficient integration at different SC levels.
Performance evaluation and benchmarking
Hamid Ghasemi; Mahyar Javid Ruzi; Mohammad Taghi Nazarpur
Abstract
Contractors help the government in carrying out construction and service projects. To reduce the risks resulting from the preparation and implementation of construction projects, the insurance industries should cooperate to include risk management. Contractors are facing many challenges regarding their ...
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Contractors help the government in carrying out construction and service projects. To reduce the risks resulting from the preparation and implementation of construction projects, the insurance industries should cooperate to include risk management. Contractors are facing many challenges regarding their insurance. Therefore, in this study, significant attention has been paid to identifying and ranking the challenges of contractor insurance in construction projects. The required information has been collected through the Delphi method and the opinions of experts in contracting companies. To identify the challenges, an open-ended questionnaire was distributed among the experienced insurance officials and 38 challenges have been identified. The relevant challenges formed the basis of a closed-ended questionnaire and the respondents were asked to re-evaluate their accuracy. Then, the approved challenges were the basis of the fuzzy best-worst method for weighing and ranking the related challenges. The results showed that the failure to provide specific consultation to contractors regarding the legal obligations of social security is the most important challenge in the field of contract insurance.
Decision analysis and methods
Davood Yaghoobi; Seyed Mahmoud Hashemi; Abdollah Naami
Abstract
This research is conducted with the aim of providing an effective advertising pattern based on social networks in educational businesses industry. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study was a group of experts ...
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This research is conducted with the aim of providing an effective advertising pattern based on social networks in educational businesses industry. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study was a group of experts including senior managers of private sector educational institutions, university professors and marketing consultants familiar with the private educational services industry that in-depth interviews were conducted with them. The selection of experts and doing interview with them continued until the theoretical saturation was reached and then stopped. Snowball sampling method was used in this research and this process continued until reaching the theoretical saturation. 9 interviews were conducted in total. Due to using the data foundation theory in this research, the main data collection tool was unstructured in-depth interviews with experts. Finally, after three open, axial and selective kinds of coding, the conceptual model of the research was designed based on a paradigm model. Also, in this study, using AHP decision method, research variables were prioritized according to experts.
Supply chain management
Arash Khosravi Rastabi; Seyed Reza Hejazi Taghanaki; Shahab Sadri; Anil Kumar; Hossein Arshad
Abstract
The objective of this study is to model a dynamic redesigning closed-loop supply chain network with capacity planning in order to minimize the costs of the network. The structure of this model consists of existing facilities including manufacturing plants, distribution and reworking centers. Any such ...
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The objective of this study is to model a dynamic redesigning closed-loop supply chain network with capacity planning in order to minimize the costs of the network. The structure of this model consists of existing facilities including manufacturing plants, distribution and reworking centers. Any such structure should change due to fluctuations in demand in order to meet customer demand. Establishing new facilities, closing the existing ones, and adding discrete capacity levels to facilities, are among the decisions which lead to necessary changes in network structure. To make the issue more realistic, it is assumed that demand and returned products are stochastic. To solve the problem, a two-stage stochastic mixed integer linear programming is modelled, followed by writing a robust counterpart of the MILP model program. An accelerated Benders decomposition algorithm is proposed to solve this model. To increase the convergence trend of this proposed algorithm, valid-inequalities and Pareto optimal cut are combined to the model. The expected performance improvement based on applying valid-inequalities and Pareto optimal cut is expressed through numerical results obtained from different samples.
Decision analysis and methods
Vahid Mottaghi; Mahdi Esmaeili; Ghasem Ali Bazaee; Mohammadali Afshar Kazemi
Abstract
With the increase of news on social networks, a way to identify fake news has become an essential matter. Classification is a fundamental task in natural language processing (NLP). Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of fake news ...
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With the increase of news on social networks, a way to identify fake news has become an essential matter. Classification is a fundamental task in natural language processing (NLP). Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of fake news classification. In this paper, new baseline models were studied for fake news classification using CNN. In these models, documents are fed to the network as a 3-dimensional tensor representation to provide sentence-level analysis. Applying such a method enables the models to take advantage of the positional information of the sentences in the texts. Besides, analyzing adjacent sentences allows extracting additional features. The proposed models were compared with the state-of-the-art models using a collection of real and fake news extracted from Twitter about covid-19, and the fusion layer was used as the decision layer in selecting the best feature. The results showed that the proposed models had better performance, particularly in these documents, and the results were obtained with 97.33% accuracy for classification on Covid-19 after reviewing the evaluation criteria of the proposed decision system model.
Supply chain management
Hamidreza Mahmoudi; Morteza Bazrafshan; Mohadeseh Ahmadipour
Abstract
In this paper, a framework for optimizing the oil condensate supply chain is modeled using mathematical planning to design and make strategic and tactical decisions. According to this framework, investment and operating costs for oil and gas transmission lines can be minimized to meet the pressure requirements ...
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In this paper, a framework for optimizing the oil condensate supply chain is modeled using mathematical planning to design and make strategic and tactical decisions. According to this framework, investment and operating costs for oil and gas transmission lines can be minimized to meet the pressure requirements and the transmission network. Also, we can minimize the production of pollutants in the chain-related sectors. In the case under study, all possible decisions are considered to consider the environmental aspects of the supply chain. Therefore, the structure and decisions of the supply chain are generally based on two objective functions, including reducing transmission and maintenance costs and pollution in treatment plants and distribution centers. The proposed model is 95% reliable, which is acceptable reliability, and can estimate goals with only 5% error. Using the proposed model will reduce costs by 31% and emissions by 51%. Also, there will be an 8% increase in the capacity of fields and refineries and an increase in exports by 65%. Using the results obtained from solving the model, we can determine the share of each petroleum product in the cost and each part of the chain in the production of greenhouse gases. According to the results, fuel oil has the highest and oils the lowest. In addition, refineries have the greatest impact, and storage tanks have the least impact on environmental pollution.
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.
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.
Computational Intelligence
Divya Aggarwal; Baishali Singh; K. Shweta Ranjan
Abstract
The recognition of pathways and identification of cars was seen with a prospective camera, which recognizes trajectories and predicts control points. The aim is to propose the location of the path. In this paper, lane detection algorithm Steering Assistance System (SAS) is introduced. Guiding helps to ...
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The recognition of pathways and identification of cars was seen with a prospective camera, which recognizes trajectories and predicts control points. The aim is to propose the location of the path. In this paper, lane detection algorithm Steering Assistance System (SAS) is introduced. Guiding helps to learn driving and anticipates the control points and defines the direction that makes it easy to learn in a potential way and a lane keeping assistance system which warns the driver on unintended lane departures. Path keeping is an important element for self-driving cars. This article describes the beginning to end adapting the approach to holding the car in the right direction.
