Multi-Attribute Decision Making
mohammad reza koleini; negin berjis; ahmad reza nematolahi
Multi-Attribute Decision Making
roshanak motofakerfard; nadereh rastghalam; hadi shirooyehzad
Abstract
Evaluation of the current system of national distribution, design network model of production and distribution of product and strategy with efficiency in order to reduce the cost of physical distribution of goods, something essential seems to be one of the most important factors in corporate profitability ...
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Evaluation of the current system of national distribution, design network model of production and distribution of product and strategy with efficiency in order to reduce the cost of physical distribution of goods, something essential seems to be one of the most important factors in corporate profitability is .The main objective of this research is how to design appropriate strategies using TOPSIS and SAW presented distribution network. For this purpose, the data were first collected, then the data was analyzed and the conclusion was reached. Company elphy Isfahan province was chosen as the model is tested. A questionnaire was used to collect data. For this purpose, a questionnaire with 10 criteria and the opinion of several experts and experts of the company was developed. The study population was elphy food production and distribution company.Analysis method, TOPSIS and SAW, respectively. Major Findings indicate that design strategies distribution network levels 2, 3, 4, 5, 1 and 6 in the methods TOPSIS and levels 1, 2, 3, 5, 6 and 4. In the SAW in order for development programs to managers were proposed . So both methods, two strategies have chosen as the best strategy.
Non-linear Optimization
Azhdar Soleymanpour Bakefayat
Abstract
In this paper, A innovative method designed to solving nonlinear optimization problems with convex object function and constrained. In this method, we define an cost function and we find variables to minimization of cost function. For create properly cost function we use K. K. T. optimal conditions. ...
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In this paper, A innovative method designed to solving nonlinear optimization problems with convex object function and constrained. In this method, we define an cost function and we find variables to minimization of cost function. For create properly cost function we use K. K. T. optimal conditions. We used Nelder-Mead without derivative optimization method to minimization of cost function. When, dimensions of problem is about 10, application shows that efficiency of Nelder-Mead method is more than the other methods. Using new mathod is easier than the similar methods. By several examples efficiency of new method are verified.
Optimization in science and engineering
Amir Parnianifard
Abstract
The quality loss function is conventional techniques in robust design terminology that consider the deviation of output from ideal point and variability as well. Mostly in practice, processes are affected by uncontrollable external factors that cause output of process to be far from ideal points with ...
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The quality loss function is conventional techniques in robust design terminology that consider the deviation of output from ideal point and variability as well. Mostly in practice, processes are affected by uncontrollable external factors that cause output of process to be far from ideal points with variability around its exact value. In this research, the common Taguchi quality loss function is applied to propose a new robust optimization model that able to choose optimal results of input variables. In this model, the quality loss function is expanded and a nonlinear optimization model is introduced in order to minimize the effect of environmental noise variables. In the end, a numerical example is presented to show the applicability of the proposed model for investigating the best levels of input variables in the noisy process.
supply chain management analyzing/modelling
seyyedmoein baharisaravi; Reza Hasan Zadeh
Abstract
Dam failure is one of the main and most important consequences of dam safety factors and the prospect of dam failure is a matter of concern in dam construction issues. Engineering science and experience in dam construction show that, on average, less than one dam annually breaks through the tens of thousands ...
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Dam failure is one of the main and most important consequences of dam safety factors and the prospect of dam failure is a matter of concern in dam construction issues. Engineering science and experience in dam construction show that, on average, less than one dam annually breaks through the tens of thousands of large dams in the world. For this purpose, this paper proposes a model to simulate the occurrence of an accident and perform logistic planning with the aim of improving logistical measures and responding to crisis situations in order to achieve the best performance in times of crisis. In this paper, we try to illustrate the failure of Shahid Rajaee Dam in Sari using simulation technique and analyze its subsequent consequences, in order to use the output information as a basic mathematical modeling information. . So at the end of the research we can clearly select the optimal routes with the least cost and transportation time.The innovation of the present study is to use a three-objective model to reduce shipping, warehousing and relief costs in the shortest time possible to manage the crisis using this model.
Multi-Attribute Decision Making
Abazar Keikha
Abstract
Purpose: The aim of this paper is to propose a new extension of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to be applied with Hesitant Fuzzy Numbers (HFNs).Methodology: At first, the uncertainty of all enteries of evaluation matrix have been modeled by HFNs. ...
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Purpose: The aim of this paper is to propose a new extension of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to be applied with Hesitant Fuzzy Numbers (HFNs).Methodology: At first, the uncertainty of all enteries of evaluation matrix have been modeled by HFNs. Then, each step of the standard model of TOPSIS method will be updated, using the newly introduced HFNs’ mathematical tools, such as distance measures and aggregation operators of HFNs. The proposed method will be used to solve a Multi-Attribute Decision Making (MADM) problem. Finally, the credibility and comparison analysis of the obtained ranking order will be discussed.Findings: In this paper, the TOPSIS method as a popular method for solving MADM problems has been developed to be applied with HFNs.Originality/Value: In this paper, the TOPSIS method as a popular method for solving MADM problems has been developed to be applied with HFNs.
Decision based on Neural Networks/ Deep Learning
Mohamad Ali Khatami Firoz Abadi; Mona Jahangir Zade; Amir Mazyaki; Seyed Soheil Fazeli
Abstract
Purpose: Nowadays insurance companies, same as other companies, are facing massive competition. This issue indicates the value of customer loyalty also a predictive model. Customers play a crucial role in the sustainability of organizations by constant repurchasing. Companies with loyal customers have ...
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Purpose: Nowadays insurance companies, same as other companies, are facing massive competition. This issue indicates the value of customer loyalty also a predictive model. Customers play a crucial role in the sustainability of organizations by constant repurchasing. Companies with loyal customers have more market share, and more money may return on investment. This article's main aim is to identify the factors affecting customer loyalty in insurance companies.Methodology: This research was quantitative, analytical-descriptive. In gathering information, Data was collected through the survey, and the findings are practical. In this way, two methods, Confirmatory Factor Analysis (CFA) and Artificial Neural Networks (ANN) were used. For localizing the factors extracted from other similar prior literature, first, the elements were examined by CFA with SMART PLS application due to some conflicts in the literature to evaluate whether each factor affects customer loyalty or not. Then, the elements were introduced to the ANN for training by this program.Findings: In this article, by using the MORGAN table, the sample size detected 384 people in 0.05 error. Questionnaires were distributed randomly between four Iranian insurance companies, ASIA insurance company, ALBORZ insurance company, and PARSIAN insurance company. Based on Confirmatory Factor Analysis, elements of commitment, perceived quality, trust, perceived value, empathy, brand image, the attraction of other alternatives, and customer satisfaction impact the customer loyalty of insurers in these companies. The cost of change, nevertheless, did not have a significant effect on customer loyalty. Then, the factors used as inputs for the multi-layer perceptron training also customer loyalty are indicated as output. The model was designed with eight inputs, 110 nodes in the hidden layer, and one output the error was E= 0.00992 and the regression = 0.98684.Originality/Value: the finding of this research is, expanding a model for predicting customer loyalty in Iranian insurance companies.
Multi-Attribute Decision Making
Abbas Jahangiri
Abstract
Purpose: Selection of the appropriate process is one of the most important issues prior to design and construct any wastewater treatment plant. Considering the importance of this issue, current study was carried out to selecting the best wastewater treatment process in city of Farmahin.Methodology: In ...
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Purpose: Selection of the appropriate process is one of the most important issues prior to design and construct any wastewater treatment plant. Considering the importance of this issue, current study was carried out to selecting the best wastewater treatment process in city of Farmahin.Methodology: In this descriptive study that conducted in 2021, three wastewater treatment processes named: Activated Sludge with nitrogen and phosphorus removal, Extended Aeration with nitrogen and phosphorus removal and Membrane Bioreactor were considered as problem alternatives. The required data was obtained by distributing a researcher-made questionnaire consisting of cost, technical, environmental and managerial criteria among 21 experts. The weight of each attribute was determined using the Entropy method and finally, decision matrix was processed by using one of the newest multiple attribute decision making methods called “Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS)”. It should be noted that all calculations were performed using Excel 2016 software.Findings: The results showed extended aeration with nitrogen and phosphorus removal with 0.758 utility function has taken first priority, activated sludge with removal of nitrogen and phosphorus with a 0.723 utility function has taken second priority and finally membrane bioreactor with 0.576 utility function has taken last priority. Therefore, the best wastewater treatment process in the city of Farmahin is extended aeration with nitrogen and phosphorus removal.Originality/Value: In this paper, by using one of the newest multiple Attribute decision making methods called "MARCOS", the best wastewater treatment process for the city of Farmahin was selected. The results of this research are very useful for the Markazi Province Water and Wastewater Company.
Decision based on Semantic relatedness
Gelayol Niazadeh; Fatemeh Baratlou; Seyed Reza Salehi Amiri,; Abbasali Ghaiyoomi; Aliakbar Rezaei
Abstract
Language is the most important factor in transmitting culture and heritage from the past and plays a decisive role in explaining and organizing the thoughts and beliefs of individuals - in the present and future of society. In this paper, it is aimed to explain the role of foreign languages in Islamic ...
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Language is the most important factor in transmitting culture and heritage from the past and plays a decisive role in explaining and organizing the thoughts and beliefs of individuals - in the present and future of society. In this paper, it is aimed to explain the role of foreign languages in Islamic Republic of Iran national and international cultural policy makings that has been challenged the previous equations and assumptions in the era of the globalization project according to the cons and the globalism process by the pros. The research method was descriptive-survey and data collection tool was a researcher-made questionnaire consisting of 25 questions. The statistical population of the study includes the cultural, political, social and linguistic elites of the country and the results show that the social, economic, political and cultural components are the most important components in Iran’s national and international cultural policy makings confronting foreign languages. Finally, according to the threats and opportunities of the internal and external environment, a new doctrine was presented in order to improve existing scientific theories, and then the components and indexes were ranked using the voting optimization model, so the previous step was approved.
Multi-Attribute Decision Making
roshanak motofakerfard; hadi shirouyehzad
Abstract
The main objective of this research is, how can suitable place to build a cement factory using LINMAP provided. At first, data collection and analysis was performed on them. Industrial three areas of Isfahan province were selected as the test model was. For this purpose, a questionnaire with 8 standard ...
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The main objective of this research is, how can suitable place to build a cement factory using LINMAP provided. At first, data collection and analysis was performed on them. Industrial three areas of Isfahan province were selected as the test model was. For this purpose, a questionnaire with 8 standard was designed with a few experts cement industry. The study population consisted of a candidate site for the construction of a cement factory was. Major Findings indicate that measures environmental conditions and access to the labor force weights respectively 0.862 and 0.138 have been selected for decision-making. Also, Mahyar areas with Rank 1 and Rank 2 in the order of Aminabad and Natanz has been proposed for development programs to managers. Finally, our study also discussion of sensitivity analysis was performed.The main objective of this research is, how can suitable place to build a cement plant using the method presented LINMAP
meta-heuristic algorithms
Ehsan Aghdaee; Ali Husseinzadeh Kashan
Abstract
In managing a project, reliable prediction is an essential element for success. Project managers are always looking for controlling their projects to make sure the the project is within acceptable limits. For a long time, the earned value management (EVM) for pursuing time performance and the cost of ...
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In managing a project, reliable prediction is an essential element for success. Project managers are always looking for controlling their projects to make sure the the project is within acceptable limits. For a long time, the earned value management (EVM) for pursuing time performance and the cost of the project has been used. However, using this method to valuate project time performance by utilizing the time performance index (SPI) by researchers and practitioners has been faced with serious criticism. Therefore, the present study proposes a framework for assessment and prediction of the temporal performance of each of the thread activities in project management. In this framework, using the multi objective league championship algorithm (MOLCA), the initial plan of the projects is optimized and then via using the Kalman Filter prediction method, project execution planning is done such that the projects in conditions of uncertainty could be forecasted and ahead horizon being demonstrated accurately with the least error for project managers. In this paper, in order to ensure the quality of the solutions, the output of the algorithm is compared with genetic algorithms (NSGII) and particle swarm optimization (MOPSO), where results demonstrate the superiority of the proposed algorithm.
Decisions in new businesses
Seyed Fakhreddin Fakhrehosseini; Omid Aghaei Meybodi
Abstract
The present paper presents the possibility of predicting firms' bankruptcy with Sprint, Altman, Fulmer, Zmijewski and Mckee Genetic models among companies in the Tehran Stock Exchange in a different way from previous research to introduce companies which have the potential for higher bankruptcy with ...
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The present paper presents the possibility of predicting firms' bankruptcy with Sprint, Altman, Fulmer, Zmijewski and Mckee Genetic models among companies in the Tehran Stock Exchange in a different way from previous research to introduce companies which have the potential for higher bankruptcy with a comparative approach among the models. To achieve this goal, 75 companies that are selected not covered base on 141 of the Commercial law. Required data for the 10 years (86-95) has been compiled. According to the results in each of the above models, some companies were identified as high-risk probability companies, and then companies that were identified as most likely to be bankrupt in most of these models. The results also show that, with the exception of Mckee model, in four other models, three companies with high bankruptcy probability were included. Among these four models, Zmijewski model has a higher coefficient of determination, hence we can say that relative to Other models have been more accurately predicted for bankruptcy and have a significant role in corporate bankruptcy among financial ratios, debt ratios, asset turnover, and asset returns.
Data Envelopment Analyses
Abbasali Noora; Faranak Hosseinzadeh Saljooghi; Maryam Khodadadi
Abstract
In the real world, there are decision-making units in which the production process can be considered as a two-stage or multi-stage process. In order to evaluate these types of units, the network data envelopment analysis method is used. In this paper, Two-stage units have been investigated, which in ...
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In the real world, there are decision-making units in which the production process can be considered as a two-stage or multi-stage process. In order to evaluate these types of units, the network data envelopment analysis method is used. In this paper, Two-stage units have been investigated, which in the two-stage process are the outputs of the first stage of the second stage inputs, which are referred to as "middle sizes".The purpose of this research is to determine the most effective scale of the production unit scale using a two-step process based on the demand level.In this regard, while determining the units of MPSS with ordinary DEA methods, we will generalize it in two-stage models.Then, the maximum and minimum amount of production, the production units that are in the most efficient scale of the scale, are obtained at each of the stages separately and then generalized for the whole process.We consider supply and demand as two output indicators and we determine the demand level for each step separately and then the whole process so that we can obtain the maximum and minimum amount of demand.
Combinatorial Optimization
Ahmad Yousefi Hanoomarvar; Maghsoud Amiri; Laya Olfat; Alireza Naser Aadrabadi
Abstract
Purpose: The proposed model is a time-cost-quality trade-off model with three objective functions: minimizing project completion time, minimizing total project cost, and maximizing total quality of activities in a PERT network with multi-mode activities.
Methodology: After presenting the appropriate ...
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Purpose: The proposed model is a time-cost-quality trade-off model with three objective functions: minimizing project completion time, minimizing total project cost, and maximizing total quality of activities in a PERT network with multi-mode activities.
Methodology: After presenting the appropriate mathematical model, based on the design of the experiments, the possible levels of each decision variable were determined. Then, using the simulation process, random values of decision variables and response variables were obtained each time, and by using neural networks, we established a neural network model. To solve this model, two algorithms NSGA-II and MOPSO were used.
Findings: To evaluate the efficiency of the model, the designed model was implemented in the maintenance department of Abtin Ardakan Steel Company. According to the results, it is found that the NSGA-II algorithm has better performance than the MOPSO algorithm.
Originality/Value: In this paper, a model was presented that by eliminating unrealistic assumptions and taking into account the realities of the project is closer to reality than the models presented in this field and has more application in practice.
stochastic/Probabilistic/fuzzy/dynamic modeling
Ali Mahmoodirad; Marzieh Salehi-Dareh-Barik; Rohollah Taghaodi
Abstract
Uncertainty is one of the most important factors which affect transportation models. As the value of most of the parameters in real-word problems are not clear, this paper represent a cost-based transportation problem with type-2 fuzzy parameters. Applying possibility theory, the fuzzy objective function ...
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Uncertainty is one of the most important factors which affect transportation models. As the value of most of the parameters in real-word problems are not clear, this paper represent a cost-based transportation problem with type-2 fuzzy parameters. Applying possibility theory, the fuzzy objective function and fuzzy constraints are formulated by a credibility measure. In addition, type-2 fuzzy variables are crisped using possibillistic critical value reduction method, in order to convert the main model into two mixed-integer sub-models which are solvable by a parametric programming approach. A numerical example including crisp demand and cost values but fixed and variable probability distributions is solved by the proposed approach. The results prove the effectiveness and flexibility of the proposed approach.
stochastic/Probabilistic/fuzzy/dynamic modeling
Heibatolah Sadeghi; Anwar Mahmoodi
Abstract
This paper considers multi-period serial production systems with Periodic order quantity (POQ) policy, lead-time uncertainties and demand dependent on the price. It is assumed that actual lead-time for each stage is probabilistic with known distribution and ordering system is multi-period. During the ...
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This paper considers multi-period serial production systems with Periodic order quantity (POQ) policy, lead-time uncertainties and demand dependent on the price. It is assumed that actual lead-time for each stage is probabilistic with known distribution and ordering system is multi-period. During the production at each stage, the items may be produced in a longer time than it was scheduled, causing a delay in production at this stage and this may result in backorders of the finished product. It is assumed in this case that a fixed percentage of the shortage is backlogged and other sales are lost. The objective of this paper is to find the pricing of the unit product, planned lead-time and periodicity with quantity (POQ) policy in order to maximize the total system profit.
Non-linear Optimization
Narges Araboljadidi
Abstract
In this paper, we present a method for charaterizing the solution set of nonconvex optimization problems via their dual problems. In fact, the constrainted optimization problem which is considerd has pseudoconvex and locally Lipschitz functions, which are not necessarily convex and smooth, and include ...
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In this paper, we present a method for charaterizing the solution set of nonconvex optimization problems via their dual problems. In fact, the constrainted optimization problem which is considerd has pseudoconvex and locally Lipschitz functions, which are not necessarily convex and smooth, and include a wide class of non-convex non-smooth functions. In the proposed method, a dual problem is formulated to characterizations of the solution set of the primal problem in a mixed type of Wolfe type and Mond-Weir type. First, we introduce some of the properties of the Lagrangian functions associated to these problems and then we explain the proof of the characterization of their solution sets.
Data Envelopment Analyses
Mostafa Radsar; Aliyeh Kazemi; Mohammadreza Mehregan
Abstract
Purpose: It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, ...
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Purpose: It is important to consider the uncertainty in the data, and know how to deal with it when evaluating efficiency by using data envelopment analysis; since the presence of small deviations in the data can lead to significant changes in efficiency results. However, in the real world in many cases, the data is uncertain. The purpose of this paper is to present a robust model of network data envelopment analysis in order to measure efficiency in the presence of uncertainty.Methodology: A new approach to evaluate efficiency for network data envelopment analysis is first proposed. The definitive method presented in this paper involves undesirable output and can be used for different structures in network data envelopment analysis. Next by extending, the proposed model for uncertain data a new robust network data envelopment analysis model is presented for three-stage networks with undesirable outputs.Findings: The proposed model is used to evaluate the electricity regions of Iran. These regions involve a three-step process with undesirable outputs in some stages. The results show that the proposed model achieves the efficiency of the steps and the total efficiency simultaneously. In addition, the overall network efficiency score can be a basis to rank the areas.Originality/Value: The proposed model is a new model in the field of efficiency evaluation in conditions of uncertainty and having an undesirable output.
Scheduling Modeling
Ali Husseinzadeh Kashan; Saeed Afkhami; Parisa Maroofkhani
Abstract
Purpose: In this research due to the importance of the U-shaped assembly line balancing and, on the other hand, the importance of human factors and setup times, we want to develop a bi-objective mathematical model minimize the cycle time and the total cost.Methodology: Since the research problem is shown ...
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Purpose: In this research due to the importance of the U-shaped assembly line balancing and, on the other hand, the importance of human factors and setup times, we want to develop a bi-objective mathematical model minimize the cycle time and the total cost.Methodology: Since the research problem is shown to be NP-hard, NSGA-II, which is a population-based algorithm, and also SPEA-II are used to solve the problem.Findings: A mathematical model for the problem on hand is developed. We solve the problem using NSGA-II and SPEA-II. We use four criteria for analyzing the results of the mathematical model and evaluating the performance of the multi-objective evolutionary algorithms. The experimental results demonstrate that NSGA-II is superior to SPEA-II.Originality/Value: A bi-objective mathematical model for the U-shaped assembly line balancing problem considering setup-times and workers' skill is developed, and the problem is solved using two algorithms.
Optimization in science and engineering
Amir Parnianifard; Hamidreza Izadbakhsh
Abstract
Up to now, different tools have been introduced for analyses of process capability such as process capability indexes of Cp, Cpk and Cpm that developed for analyzing the capability of process and adapting the quality specifications of product. Most studies in the literature only consider the process ...
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Up to now, different tools have been introduced for analyses of process capability such as process capability indexes of Cp, Cpk and Cpm that developed for analyzing the capability of process and adapting the quality specifications of product. Most studies in the literature only consider the process with single capability variable, while there is a lack of studies that consider multi-variable processes. Cpm index has been defined with Taguchi overview over robust design. In this research, the metric Lp model has introduced to investigate the optimum decision variables by considering nominal is better quality specification and reparation Cpm index. We also expand the proposed model for such a processes with considering overall cost as well as process quality. At the end of research, numerical example has been presented to exhibit usage of proposed model for obtaining the best levels of process decision variables.
meta-heuristic algorithms
Hojatollah Rajabi Moshtaghi; Abbass Toloie-Eshlaghy; Mohammad Reza Motadel
Abstract
Purpose: In recent years, meta-heuristic algorithms and their application in solving complicated, nonlinear, and high dimensions problems have increased dramatically and the fact that meta-heuristic algorithms are used to solve complex and changing problems of real life, has caused the algorithms world ...
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Purpose: In recent years, meta-heuristic algorithms and their application in solving complicated, nonlinear, and high dimensions problems have increased dramatically and the fact that meta-heuristic algorithms are used to solve complex and changing problems of real life, has caused the algorithms world and their design to be very dynamic and alive; that's why new algorithms are constantly being created. Hence, the purpose of this research is to introduce a novel meta-heuristic algorithm called Military Optimization Algorithm (MOA). Methodology: Inspired by military operations, the proposed algorithm was designed and presented. After coding, Standard test functions and benchmark algorithms were determined to evaluate the performance of the algorithm.Findings: The performance of new algorithm is analyzed by 23 standard test functions and compared to 8 benchmark meta-heuristic algorithms including: Genetic Algorithm, Particle Swarm Optimization, Artificial Bee Colony, Shuffled Frog Leaping Algorithm, and Imperialist Competitive Algorithm, Grey Wolf Optimizer, Whale Optimization Algorithm, and Grasshopper Optimization Algorithm, by considering three indices of "average answers", "time complexity of algorithm (speed)" and "Convergence speed/ time". The results show the excellent performance of the proposed algorithm.Originality/Value: In this paper, inspired by military operations, a novel meta-heuristic algorithm called MOA is introduced. It is population-based and stable with "random search", "dividing solution space into several regions and allocating a part of the population to each region", "cavalry search", and "infantry search".
Data Envelopment Analyses
Seyed Hamzeh Mirzaei
Abstract
One of the problems of based models on data envelopment analysis (DEA) for ranking preference voting systems is that it allows each alternative have its own weight vector. Therefore, alternatives are evaluated with different weight vectors. In this study, we propose a model based on fuzzy logic to solve ...
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One of the problems of based models on data envelopment analysis (DEA) for ranking preference voting systems is that it allows each alternative have its own weight vector. Therefore, alternatives are evaluated with different weight vectors. In this study, we propose a model based on fuzzy logic to solve the weaknesses of the previous models. This model is based on the solving of multi-objective programming models with the help of fuzzy logic, in this way it providing a vector of common weights, and finally, we can rank the alternatives.
Multi-Attribute Decision Making
Jalal Naderi; Mohamad Nadiri; Fatemeh Zarei
Abstract
Purpose: The credit risk and non-performing loans of banks are among the most important problems of the banking system in Iran. And according to available statistics, the average default of loans and non-performing loans of banks in Iran is much higher than the global average. The main purpose of this ...
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Purpose: The credit risk and non-performing loans of banks are among the most important problems of the banking system in Iran. And according to available statistics, the average default of loans and non-performing loans of banks in Iran is much higher than the global average. The main purpose of this study is to identify and analyze the basic and important factors affecting credit risk in the Iranian banking system.Methodology: For this purpose, first, using the method of guided interviews with twenty experts and credit risk managers of the country's banking sector, who were selected by the snowball method, the most important factors affecting credit risk were identified; then, these factors were returned to the experts for ranking in the form of a pairwise comparison questionnaire, and finally, the important factors affecting this risk, along with their sub-factors were analyzed using denp technique (the dematel based analytic network process).Findings: The results of the research show that the macroeconomic factors are the most important factor as well as instability in macroeconomic environment, failure to take timely and inappropriate actions with defaulters, poor and inadequate credit monitoring, ordered loans, and lengthy and time-consuming judicial procedures are the most important factors affecting risk credit in Iranian banking.Originality/Value: The distinguishing feature of this study from other similar studies is the use of DANP technique to investigate the relationships between factors and sub-factors.
Seyyedeh Fatemeh Aghajani Mir; Fatemeh Zahra Rajabi kafshgar; Alireza Arab
Abstract
Purpose: Today, the advent of blockchain technology has changed the way businesses do business, the size and scope of different organizations. One of these areas is the supply chain, which has many stakeholders, and blockchain, with its unique features, effectively responds to the various challenges ...
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Purpose: Today, the advent of blockchain technology has changed the way businesses do business, the size and scope of different organizations. One of these areas is the supply chain, which has many stakeholders, and blockchain, with its unique features, effectively responds to the various challenges in this area. Implementing this technology, like other technologies, has many challenges. Hence, these challenges must be carefully identified and analyzed to minimize their adverse impacts to use this technology effectively. In this regard, the present study aims to identify and prioritize the challenges of implementing blockchain technology in the supply chain based on the Bayesian BWM as one of the newest multiple attribute group decision-making methods.Methodology: At first, after reviewing the research literature, the challenges were identified. Then, the Bayesian BWM method determined the importance of these challenges in the case study.Findings: The results showed that security, technical and organizational challenges are the most important challenges for the company in implementing this technology, respectively. Also, among all sub-indicators of research challenges, poor scalability, privacy/confidentiality of the information, and cyberattacks have the most importance, respectively.Originality/Value: This study studied the challenges of implementing blockchain technology as a new technology in supply chains using one of the newest multiple attribute group decision-making methods (Bayesian BWM). Based on the research results, practical and research suggestions were presented
stochastic/Probabilistic/fuzzy/dynamic modeling
Ali Sahleh; Maziar Salahi; Sadegh Eskandari
Abstract
Purpose: The aim of this paper is to present an enhanced variant of Twin Parametric-Margin Support Vector Machine (TPMSVM) that improves classification performance.Methodology: By replacing a variable in the objective function, we keep the samples of one class farther from the parametric margin hyperplane ...
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Purpose: The aim of this paper is to present an enhanced variant of Twin Parametric-Margin Support Vector Machine (TPMSVM) that improves classification performance.Methodology: By replacing a variable in the objective function, we keep the samples of one class farther from the parametric margin hyperplane of the other class.Findings: The enhanced model is convex for both linear and nonlinear cases. Also, numerical experiments on UCI datasets show that the enhanced model performs better compared to two similar models for both linear and nonlinear cases.Originality/Value: The previous studies of TPMSVM that increased the accuracy through approaches such as assigning weights to data sample, converting it into an unconstrained model and adding a new term in the objective function, did not guarantee that all samples will be far and on the negative side of the margin hyperplane. However, this study provides an approach to overcome this disadvantage of TPMSVM.