Data Envelopment Analyses
nasrin bagheri mazraeh; Mohsen Rostami Mal Khalife; Meysam Varzi
Abstract
Purpose: Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance ...
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Purpose: Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance indicators. This is despite the fact that DEA is one of the most effective tools for measuring and evaluating efficiency. Nevertheless, identifying the relationship between efficiency estimates and commonly accepted financial measures of performance could guide benchmarking activities, pricing decisions, and regulatory monitoring.Methodology: In this paper, the DEA super-efficiency formula is tested in two profitability models. Four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, were calculated with a developed profitability model; besides, the growth rate of assets was calculated with main profitability model and all the aforementioned ratios addressed a significant association with efficiency estimates.Findings: In this study, the DEA super-efficiency formula is tested in two profitability models for 15 banks for two years. The correlation obtained is generally low. However, the four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, in the EPM model and asset growth rate in the CPM model have a significant relationship with performance estimates. Finally, the results indicate poor credit quality in Iranian banks in 1397-1397.Originality/Value: In this study, for the first time, the nature of the relationship between performance and key performance indicators has been estimated. DEA technique has been used to purposefully identify criteria for analyzing financial ratios.
supply chain management analyzing/modelling
Farzaneh Rezaee; Nazanin pilevari
Abstract
Purpose: In the current complicated supply chains, sustainability and two social and environmental perspectives have significantly caught researchers’ attention due to their significant role in cost reduction. The present study aims to propose a sustainable multi-tier supply chain model for power ...
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Purpose: In the current complicated supply chains, sustainability and two social and environmental perspectives have significantly caught researchers’ attention due to their significant role in cost reduction. The present study aims to propose a sustainable multi-tier supply chain model for power plant products for industrial and manufacturing factories.Methodology: To this end, a mathematical model was proposed with three objectives: maximizing the social responsibility, minimizing the emission of environmental pollutants, and reducing the costs of the supply chain. The whale and genetic metaheuristic algorithms were employed to propose and solve the model since sustainable supply chain planning was considered an NH-hard problem.Findings: In order to solve the proposed model, the experimental sample was designed in three groups including small, medium, and large in terms of the data of Atmosphere Company. The results of whale optimization and genetic algorithms were compared according to the comparative indices of quality, dispersion, uniformity, and solving time.Originality/Value: According to the results, the whale algorithm was able to provide higher quality and near-optimal solutions than genetic algorithm; in addition, by comparison, it could efficiently explore and extract possible areas of the solution in terms of quality and dispersion indices. However, a shorter amount of time was required for genetic algorithm to uniformly find solutions.
stochastic/Probabilistic/fuzzy/dynamic modeling
Hamid Tabatabaee; Shirin Rikhtegar Mashhad
Abstract
Nonlinear dynamical systems modeling is one of the real challenges of the real world due to the nonlinear and variable nature of time. In this paper, an Online Self-organizing Takagi-SugenoNeuro-Fuzzy System(OSO-NFS) for dynamic Nonlinear System Identification is proposed. OSO-NFS is built based on radial ...
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Nonlinear dynamical systems modeling is one of the real challenges of the real world due to the nonlinear and variable nature of time. In this paper, an Online Self-organizing Takagi-SugenoNeuro-Fuzzy System(OSO-NFS) for dynamic Nonlinear System Identification is proposed. OSO-NFS is built based on radial basis function(RBF). The algorithm has the ability to adaptive adjustment of the system’s parameter and continuous evolution of the system’s structure. Structure identification and parameters estimation are performed simultaneously. The OSO-NFS starts with no hidden neuron. In structural learning, the proposed OSO-NFS uses a two-step algorithm to create a suitable number of rules. A pruning algorithm is used for detecting inactive hidden units and removing them as learning progresses. The weighted recursive least square (WRLS) algorithm is used to adjust all the consequent parameters. Finally, two benchmark examples of nonlinear system identification are demonstrated to show the effectiveness of the proposed method, compared with the other methods. The accuracy of this modeling has been compared with the other methods according to two criteria of the number of neurons (rules) and the root mean square error. According to the results, the average percentage of improvement of the answers in the number of rules obtained in comparison to the chosen method in the modeling of these two systems in both the noise and non-noise modes in the first example is 42.35% and in the second example is 29 %.
Forecasting Models/ Time Series
Moeen Sammak Jalali; Seyed Mohammad Taghi Fatemi Ghomi
Abstract
Among various applications of time series, applying this concept in production industries with the intention of pre-detecting failure times of machines and implementing maintenance tasks, is considered as one of the most valuable activities in the automotive industries. With this regard, this article ...
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Among various applications of time series, applying this concept in production industries with the intention of pre-detecting failure times of machines and implementing maintenance tasks, is considered as one of the most valuable activities in the automotive industries. With this regard, this article embarks on applying time series analysis as well as quality assurance concepts to detect failure times and implement proper actions. With this regard, we will analyze the data derived from maintenance department of the company. Then we determine influential factors on parts failure by means of quality assurance concepts.
Decisions in new businesses
Mohammad Mousakhani; Fateme Saghafi; Mohammad Hasanzade; mohammad ebrahim sadeghi
Abstract
Economic development of countries is associated with development of high technologies. So policy making for these technologies is one of the most important interests of policy makers. Technological innovation system, as a most important approaches in technology policy, has developed increasingly. Therefore, ...
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Economic development of countries is associated with development of high technologies. So policy making for these technologies is one of the most important interests of policy makers. Technological innovation system, as a most important approaches in technology policy, has developed increasingly. Therefore, identification of the most important dimensions in this field to propose policy interventions for development of high technologies is credential. We used metasynthesis to integrate and combine previous studies in the field. The research Statistical population is 280 document with the keyword of technological innovation system in scopus database until end of 2018.at the end, contributions of 52 article used in the final framework. In order to evaluate the quality of the research, we used Critical Appraisal Skills Program (CASP) method. Also, kappa index used to verify the reliability of the research. Regard to developing the framework by using the elements of previous frameworks, the framework has content validity. Also the content validated by 5 experts in innovation study field. We propose the comprehensive framework of TIS with 10 dimensions and 102 activities. The main dimensions are: development, exchange and diffusion of knowledge, entrepreneurial activities, guidance of search, market formation, resource mobilization, legitimation, policy and coordination, creating structure, weaken the regime, exploit the regime. Also, attention to the context and using the contingent view to response the opportunities and threats was proposed as complementary to the framework. developing high technologies is a very complex and multi-dimensional issue which requires to identify the dynamics of innovation systems. One dimensional perspective to technology development and mere attention to knowledge creation and R&D, would not lead to technology development. Therefore, in order to policy in this field, attention to dimensions and elements which is identified in this study could be very useful.
Multi-Attribute Decision Making
seyed esmaeil najafi; reza Behnood; mojtaba omidi rakavandi
Multi-Attribute Decision Making
saeid mojody; Atefeh Amindoost; Mehrdad Nikbakht
Abstract
Power management set of methods and strategies that can be used to optimize energy consumption. Due to the widespread use of electric energy in human life the bulk of consumption management processes associated with managing electric power consumption. The main objective is how strategies and measures ...
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Power management set of methods and strategies that can be used to optimize energy consumption. Due to the widespread use of electric energy in human life the bulk of consumption management processes associated with managing electric power consumption. The main objective is how strategies and measures to reduce energy consumption in cement industry solutions identified using fuzzy AHP method ranked. The solution is to collect 23 7 Index of literature, interviews and brainstorming with experts, specialists and experts were Sepahan Cement. The questionnaire and distribute them among 100 experts and professionals, decision matrix Vmatrys was paired comparisons. Then the whole matrix hourly data are converted into fuzzy numbers and fuzzy decision and paired comparisons with average data matrices 23 and 7 indicators were formed solution. At the end of 23 strategies were ranked using fuzzy AHP. Results indicate that after identifying ratings and rating solutions, solutions "of hot exhaust gases heat recovery and power generation," as the highest rank, respectively. Innovation of this study is to see the phased approach of decision-making, to identify and rank the strategies and measures to reduce electrical energy consumption is in cement Sepahan
multi objective decision making
Mehdi Allahdadi; Fatemeh Salary Pour Sharif Abad; Hassan Mishmast Nehi
Abstract
Purpose: Determining efficient solutions of the Interval Multi Objective Linear Fractional Programming (IMOLFP) model is generally an NP-hard problem. For determining the efficient solutions, an effective method has not yet been proposed. So, we need to have an appropriate method to determine the efficient ...
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Purpose: Determining efficient solutions of the Interval Multi Objective Linear Fractional Programming (IMOLFP) model is generally an NP-hard problem. For determining the efficient solutions, an effective method has not yet been proposed. So, we need to have an appropriate method to determine the efficient solutions of the IMOLFP. For the first time, we want to introduce algorithms in which the strongly and weakly efficient solutions of the IMOLFP are obtained.Methodology: In this paper, we introduce two algorithms such that in one, strongly feasible of inequalities and in the other, weakly feasible of inequalities are considered (A system of inequalities is strongly feasible if and only if the smallest region is feasible, and a system of inequalities is weakly feasible if and only if the largest region is feasible). We transform the objective functions of the IMOLFP to real linear functions and then convert to a single objective linear model and then in each iteration of the algorithm, we add some new constraints to the feasible region. By selecting an arbitrary point of the feasible region as start point and using the proposed algorithms, we obtain the strongly and weakly efficient solutions of the IMOLFP.Findings: In both proposed algorithms, we obtain an efficient solution by selecting the arbitrary points, and by changing the starting point, we obtain a new point as the efficient solution.Originality/Value: In this research, for the first time, we have been able to obtain the strongly and weakly efficient solutions of the IMOLFP.
Decision based on Neural Networks/ Deep Learning
Yousef Ebrahimi; Yagoub Alavi Matin; Sahar Khoshfetrat; Hasan Refaghat
Abstract
Purpose: Banks as a service and financial economic enterprise, while accompanying the economic programs of countries, seek to benefit their stakeholders. In order to achieve this goal, they must be able to equip and allocate their resources optimally. One of the important issues is to identify the factors ...
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Purpose: Banks as a service and financial economic enterprise, while accompanying the economic programs of countries, seek to benefit their stakeholders. In order to achieve this goal, they must be able to equip and allocate their resources optimally. One of the important issues is to identify the factors affecting the absorption of resources that the purpose of this study is to provide a suitable model to identify the factors affecting the supply of resources.Methodology: To achieve the purpose of the research, by reviewing the research background, mission of the bank and the opinions of banking experts, 62 factors were presented in the form of a questionnaire. After approval by banking experts, the questionnaire was distributed to a sample of 30 employees of Tejarat Bank in Zanjan province for pre-testing. Then its reliability was tested and confirmed by Cronbach's alpha. After field collection of research data, the effective components were divided into two main groups of external and internal organizational factors. Then the factors within the organization into four subgroups; Financial, physical, service and communication and human factors were separated. Finally, the main research model was extracted using the model of unattended neural networks (self-organized maps) and the research data were analyzed.Findings: Research findings show that, From the set of factors affecting the provision of banking resources, communication and human factors had the most impact and external factors had the least impact. Also, due to the lack of similarity between the models of research input vectors, the correlation between each of the factors affecting resource equipping was not confirmed.Originality/Value: In this study, using a new approach of neural network model (self-organized mapping) to identify and weigh the factors affecting the equipping of bank resources, the findings of which help to develop the literature in the field of resource equipping.
Multi-Attribute Decision Making
Meysam Azimian; Abbas Miranzadeh
Abstract
The Goal of this research is using of Fuzzy TOPSIS, one of the method of multi attribute decision making (MADM), for Selection the Optimum Place for Esfahan PIHO Clinic from exist options.In this research, after organizing a decision making team and identification of indexes may influence the clinical ...
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The Goal of this research is using of Fuzzy TOPSIS, one of the method of multi attribute decision making (MADM), for Selection the Optimum Place for Esfahan PIHO Clinic from exist options.In this research, after organizing a decision making team and identification of indexes may influence the clinical processes, the PIHO Clinic options were weighted by Fuzzy TOPSIS approach. Firstly, two options were selected for evaluation by Satisfying Method. Then indices for evaluating options were estimated by defining the indices for evaluating each one, determining their relative status to indices and fuzzy TOPSIS method. The results are only assigned for a particular time section and under controlled organization. The main conclusion is shown, using this method may invoke as a useful management tool for organization decisions. The invention seen in this paper is an integrated method of Fuzzy and MADM to selection the best place for clinic in Petroleum Industry Health Organization.
Decisions in new businesses
Aitak kor dordaei; Parviz Saeidi
Abstract
Understanding behavioral accounting has a lot to do with studying human aspects of finance. This is because the research focuses on users of financial reports and their characteristics often assumes that financial information is in impartial, non-discriminatory and worthless. However, the information ...
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Understanding behavioral accounting has a lot to do with studying human aspects of finance. This is because the research focuses on users of financial reports and their characteristics often assumes that financial information is in impartial, non-discriminatory and worthless. However, the information that investors and stakeholders in the capital market use to make economic decisions are provided by accountants who use their professional judgments when interpreting and applying accounting standards. The purpose of this paper is to examine the effect of accounting role on financial behavior. A questionnaire was used to infer the research hypotheses. This questionnaire was distributed among 288 investors in 1396. The main hypothesis of the relationship between the perception of accounting standards and financial behavior was investigated. Findings show that there is a positive and significant relationship between the perception of accounting standards and financial behavior.
supply chain management analyzing/modelling
Masoud Rabbani; Maryam Tohidi Fard; Mohammad Partovi; Hamed Farrokhi-Asl
Abstract
Todays, meeting the healthcare needs of patients at home has many benefits. By providing regular and timely healthcare servicing, in addition to reducing costs, the patient's recovery process also speeds up. In this paper, a multi-depot vehicle routing problem is considered with regard to time windows ...
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Todays, meeting the healthcare needs of patients at home has many benefits. By providing regular and timely healthcare servicing, in addition to reducing costs, the patient's recovery process also speeds up. In this paper, a multi-depot vehicle routing problem is considered with regard to time windows and fuzzy demands. This paper attempts to optimize provided mathematical formulation in such a way that the distance traveled, total travel time, the number of transportation vehicles and transportation cost be minimized; also by taking the hard time window to meet patients , patient satisfaction rate will increase. This is a complex and difficult problem, and it takes a long time to solve it through linear programming and existing software. Therefore, in this paper, two general approaches including genetic algorithm and particle swarm optimization are used to tackle the problem. The response surface methodology (RSM) has been used to set parameters for meta-algorithms. To illustrate the efficiency of proposed algorithms, a number of test problems are solved and computational results are compared with the solutions obtained with the GAMS software.
Data Envelopment Analyses
Ehsan Vaezi; Mehdi Memarpour
Abstract
Banks are among the economic centers of the country, whose performance regarding promotion of productivity and efficiency, leads to economic development of the country. Accordingly, investigation of the status of the performance and efficiency of a bank will be influenced by the performance and efficiency ...
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Banks are among the economic centers of the country, whose performance regarding promotion of productivity and efficiency, leads to economic development of the country. Accordingly, investigation of the status of the performance and efficiency of a bank will be influenced by the performance and efficiency of that bank’s branches. The aim of this study is to investigate the efficiency and ranking of 121 branches of a certain private bank in Tehran. For this purpose, first two-stage data envelope analysis has been used to obtain the efficiency of banks accurately using 7 indices as the input variable, 4 indices as the intermediate variable, and 1 index as the output variable. The results of the research indicated that in the first stage of the two-stage data envelope analysis, 51 branches were found to be efficient, which was reduced to 18 branches in the second stage. As the accurate efficiency of each branch was determined following two stages, for ranking the branches that had an efficiency of one, Sexton, Anderson-Peterson and Charnes-Cooper efficiency method was employed. In the last stage, using Borda technique, the results obtained from the previous models were combined and the final ranking of the bank’s branches was determined.
Optimization in science and engineering
Mohammad Namakshenas; Mohammad Mahdavi Mazdeh
Abstract
Purpose: The chemical attributes of Technetium-99m have made it popular for most medical imaging procedures. However, in recent years, the decay product of molybdenum-99, i.e., technetium-99m, has become expensive, and its routine availability can no longer be taken for granted. We proposed scenarios ...
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Purpose: The chemical attributes of Technetium-99m have made it popular for most medical imaging procedures. However, in recent years, the decay product of molybdenum-99, i.e., technetium-99m, has become expensive, and its routine availability can no longer be taken for granted. We proposed scenarios to maximize the throughput of Technetium-99m which is used to produce radiopharmaceuticals in a medical imaging center.Methodology: We proved a recursive function to imitate the decay dynamics of Technetium-99m, which is used in 80 percent of medical imaging. Then, we proved necessary and sufficient optimality analysis for this function.Findings: We found optimal scenarios for distributing the radiopharmaceuticals into elusion periods according to clinical considerations.Originality/Value: We developed a rigorous mathematical model based to maximize the throughput of radiopharmaceuticals in a molecular imaging center.
stochastic/Probabilistic/fuzzy/dynamic modeling
Ahmad Poordarvish; bahador hoseini
Abstract
Armero and Bayarri get Bayesian estimation from traffic intensity in M/M/1 model in 1994. Sharma and Kumar get Bayesian and classical estimations of different parameters of M/M/1 model under loss function in 1999. Furthermore, use of classical methods to estimate unknown parameters of previous distribution ...
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Armero and Bayarri get Bayesian estimation from traffic intensity in M/M/1 model in 1994. Sharma and Kumar get Bayesian and classical estimations of different parameters of M/M/1 model under loss function in 1999. Furthermore, use of classical methods to estimate unknown parameters of previous distribution is suggested by Mises for the first time in 1943. In this paper, Bayesian estimation and empirical Bayes of traffic intensity parameter are assessed in the M/M/1 queuing model. Estimation of the parameters of this model is presented by methods of Bayes, likelihood, and moment. The characteristics and applications of both estimators are discussed in numerical results. The quadratic theory has many uses in communication theory, computer design, etc. The statistical deduction in quadratic process and quadrant process estimation, such as rate of entry, service rates and traffic jams, has attracted researchers in the past few years. Suppose that the M / M / 1 queue system with an average log rate λ, as well as an average service rate of 1 / μ
Scheduling Modeling
Mohsen Bagheri; Neda Babaei Meybodi; Amir Hossein Enzebati
Abstract
Energy consumption considerations in production systems have recently attracted the attention of researchers. In conventional production scheduling models, the importance has more often been given to time-related rather than to energy-related performance measures. In this paper, we simultaneously consider ...
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Energy consumption considerations in production systems have recently attracted the attention of researchers. In conventional production scheduling models, the importance has more often been given to time-related rather than to energy-related performance measures. In this paper, we simultaneously consider energy consumption, completion time and tardiness in the presented Multi-Objective Mixed Integer Programming flow shop scheduling model. After validating the model by solving small-scale numerical examples with Weighted Sum and Epsilon-constraint method in GAMS, the large and medium-scale examples are solved via NSGA-II and SPEA-II metaheuristic-algorithms. The results prove the efficiency of the proposed algorithms.
Linear Optimization
Sajad Moradi; Gholamreza Karamali
Abstract
Shortest path problem is one of the practical issues in optimization, and there are many efficient algorithms in this area. In this issue, a network of some nodes and arcs is considered in which, each arc has a specific parameter such as distance or cost. The main objective is to find the shortest or ...
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Shortest path problem is one of the practical issues in optimization, and there are many efficient algorithms in this area. In this issue, a network of some nodes and arcs is considered in which, each arc has a specific parameter such as distance or cost. The main objective is to find the shortest or least costly route between two distinct points. By considering an additional parameter and adding a new limitation, as a capacity constraint, the problem will be closer to the real world condition. This extended issue is known as the constrained shortest path problem and has a higher complexity order and practical algorithms are needed to solve it. In this study, an effective algorithm is presented that obtains the optimal solution within a short time. In this method, a repetitive pattern is used so that, in each iteration, the relaxed model, after adding a logical cut, is solved. The results of the implementation of the proposed algorithm on different networks show its efficiency.
Data Envelopment Analyses
Fatemeh Gholami Golsefid; Behrooz Daneshian; Mohsen Rostamy-Malkhalifeh
Abstract
Purpose: The providing a proposed model pair for ranking interval data and their application to evaluate and improve the performance of a service system using results of simulation.Methodology: Mathematical techniques (data envelopment analysis) and computer simulation.Findings: By presenting proposed ...
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Purpose: The providing a proposed model pair for ranking interval data and their application to evaluate and improve the performance of a service system using results of simulation.Methodology: Mathematical techniques (data envelopment analysis) and computer simulation.Findings: By presenting proposed models pair, we were able to improve the performance of a service system by simulating different scenarios for that system. The results show that the introduced scenario could increase the efficiency of system by 22%.Originality/Value: Introducing new applied methods using mathematical models (Data Envelopment Analysis) and simulations to improve the performance of systems
meta-heuristic algorithms
javid ghahremani nahr
Abstract
With the expansion and intensification of competition, supply chain management has become one of the key issues facing economic firms, as all the activities of organizations to produce products, improve quality, reduce costs and provide services required by customers, has been affected. In this research, ...
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With the expansion and intensification of competition, supply chain management has become one of the key issues facing economic firms, as all the activities of organizations to produce products, improve quality, reduce costs and provide services required by customers, has been affected. In this research, a closed loop supply chain network include levels of (manufacturing centers, demand zones, collection centers and disposal centers) under certainty is considered. The main objective of this paper is to determine the optimal number and location of potential facilities and determine the optimal flow considering the minimization total supply chain network cost. To solve this model, a new metaheuristics algorithm called the whale Optimization algorithm has been used with novel priority-based encoding. Also, to demonstrate the high efficiency of the proposed method, 21 sample problems were designed in small, medium and large sizes, and the results obtained from the solving method and the results obtained from the methodology for solving the subject literature were compared. Comparisons between solving methods with consideration of the two averages of the objective functions and the average computational time indicate the efficiency of the proposed solution method for the comparison of the other methods of solving.
Scheduling Modeling
Roja Ruhbakhsh; Esmaeil Mehdizadeh; Mohammad Amin Adibi
Abstract
Purpose: Lot streaming, which has much attention in recent years, is an effective technique to increase production efficiency in a production system by splitting a job into several smaller parts in a multi-stage production system. But important assumptions that exist in the real-world scheduling environment ...
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Purpose: Lot streaming, which has much attention in recent years, is an effective technique to increase production efficiency in a production system by splitting a job into several smaller parts in a multi-stage production system. But important assumptions that exist in the real-world scheduling environment are always ignored. Hence, in this paper, these assumptions are discussed and the results are reviewed. In this paper, the aim is solving a multi objective mathematical model for solving hybrid flow shop scheduling problem with lot-streaming, setup time and transportation time.Methodology: At first, a multi objective mathematical programming model is presented for solving the problem. Then, by wighting method, the multi objective model convert to single objective model and GAMS software is used to solve the small size problems to show the performance of the mathematical mothel. Inspired by previous studies, two multi objective metaheuristic algorithms based on the genetic algorithm is used to solve the large-scale problems. To illustrate the performance of the proposed metaheuristic algorithms, the obtained results of the algorithms compared with GAMS outputs in single mode.Findings: To validate the proposed model, a sample is solved using GAMS software and compared with the genetic algorithm. The obtained results show the performance of the mathematical model. Then, two proposed algorithms are used to solve the large-scale problems. For this purpose, 30 instance problems are randomly generated and six indicators are used to compare the algorithms. After performing the experiments and comparing the algorithms with each other, the results show NRGA algorithm performs bether than NSGA-II.Originality/Value: In this paper, for solving a multi objective hybrid flow shop scheduling problem with lot-streamingm mathematical model with the aim of minimizing the makespan and total tardiness, the sequence-dependent setup time and the transportation time constraints between consecutive stages are considered. Since the problem is NP-hard, NSGA-II and NRGA algorithms were used to solve the proposed problem.
Fuzzy Optimization
Nemat Allah Taghi-Nezhad; Fatemeh babakordi
Abstract
Quadratic programming problem is one of the important problem of classic optimization problems that the aim is to find the maximum or minimum amount of a quadratic function under linear constraints. In this paper, the quadratic programming problem where its parameters are all nonnegative fuzzy numbers ...
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Quadratic programming problem is one of the important problem of classic optimization problems that the aim is to find the maximum or minimum amount of a quadratic function under linear constraints. In this paper, the quadratic programming problem where its parameters are all nonnegative fuzzy numbers is discussed and a new algorithm based on fuzzy operations and fuzzy arithmetic is presented where reduced the fuzzy model into three smaller and more simple crisp problem. Then, by solving these crisp models using conventional algorithms such as SQP and by combining these solutions, the optimal solution of the fuzzy problem is obtained. Finally, an example is solved to implement the proposed algorithm and show the applicability of it.
meta-heuristic algorithms
Mohammadreza Etebari; Naser Feghhi Farahmand; Soleyman Iranzadeh
Abstract
Purpose: Banks' inability to credit assessment and financial evaluation of customers and forecasting accurately the credit risk of borrowers has devastating effects on the global financial system and economic activity and have been the main causes of global financial crises in recent years.The purpose ...
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Purpose: Banks' inability to credit assessment and financial evaluation of customers and forecasting accurately the credit risk of borrowers has devastating effects on the global financial system and economic activity and have been the main causes of global financial crises in recent years.The purpose of this paper is to compile a credit forecasting model for legal customers of private banks by using meta-heuristic algorithms in the branches of Pasargad Bank in the northwest of Iran.Methodology: This research is base on the purpose of developmental research and based on the method of performing descriptive work. The statistical population of this study is in two sections of banking experts and legal customers of Pasargad Bank in the northwest of the Iran. The statistical sample size for the first community of 58 banking experts including managers, credit officials and heads of branches in with credit work experience in private banks and for the second community, 427 legal clients were selected based on targeted sampling. In order to collect data in this research, a questionnaire and documents of Pasargad Bank have been used. The validity of the questionnaire was investigated as content validity and based on the indicators of content validity ratio and content validity index. The reliability of the questionnaire was assessed using Cronbach's alpha coefficient. In order to analyze the research data, t-test, confirmatory factor analysis, multilayer neural network, genetically trained neural network, trained neural network with particle swarm optimization and trained neural network with differential evolution will be used.Findings: The research findings show that all four models are able to predict the credit predictions of the legal customers of private banks and the best way to predict the credit predictions of the legal customers of private banks is the neural network trained with differential evolution algorithm with the least amount of error compared to the other three methods.Originality/Value: In this research by using meta-heuristic algorithms, a new credit forecasting model produce for legal customers of private banks with the least amount of error.
Multi-Attribute Decision Making
Saba Amiri; Saeed Setayeshi
Abstract
Purpose: Neuromarketing is an interdisciplinary and emerging field which can be used in order to relate consumer behavior to neuroscience. So, in recent decades, the importance and interest in buying sustainable products for protecting the environment has been increased. Thus, the present study was done ...
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Purpose: Neuromarketing is an interdisciplinary and emerging field which can be used in order to relate consumer behavior to neuroscience. So, in recent decades, the importance and interest in buying sustainable products for protecting the environment has been increased. Thus, the present study was done with the aim of fuzzy analytic hierarchy process of neuromarketing evaluation criteria for sustainable products.Methodology: The research was performed with a quantitative approach and by using multiple-criteria decision analysis. For this purpose, in order to gain a deep understanding of the subject and collecting useful data, after carefully reviewing the related studies, the views of 16 experts were collected using a fuzzy hierarchical researcher-made questionnaire, which the inconsistency rate of the questionnaires confirmed reliability of them. Also, sensitivity analysis was used to ensure.Findings: The results showed that the criteria for evaluating neuromarketing are in seven categories, which based on FAHP are: accuracy, biasness, exploration of memory and emotion, information quality, usefulness, time saving, cost, respectively. Also, the alternatives of marketing for sustainable products affected by neuromarketing in order of priority are: advertising, product design and development, branding, consumer decision, pricing and distribution. Sensitivity analysis also showed that the research findings are confirmed, but in the case of two criteria of biasness and exploration of memory and emotions, there is a possibility of displacement.Originality/Value: Neuromarketing, due to the provision of high-precision and high-quality information and the reduction of bias in the analysis of results, provides the possibility of predicting consumer buying behavior and affects the marketing mix of sustainable products.
Fateme Yazdani; Mehdi Khashei; Seyed Reza Hejazi
Abstract
Purpose: This paper aims to propose a model for detecting the most profitable or the optimal Turning Points (TPs) existing in the history of the financial tool's time series. The profitable trading strategy, which is known as a tool for gaining profit in the Stock Exchange, is the strategy formed from ...
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Purpose: This paper aims to propose a model for detecting the most profitable or the optimal Turning Points (TPs) existing in the history of the financial tool's time series. The profitable trading strategy, which is known as a tool for gaining profit in the Stock Exchange, is the strategy formed from the profitable trading points. Trading points, in the corresponding literature, are known as TPs. TPs prediction is a tool for the achievement of a profitable trading strategy. The first step for predicting TPs is to detect TPs existing in the history of the financial tool's time series. The profitability of the detected TPs has a direct effect on the profitability of the predicted TPs. Given this, the literature has always tried to increase the profitability of the detected financial TPs. A complete review of the literature, by researchers, indicates that none of the existing methods can detect the optimal financial TPs.Methodology: This paper implements the problem of detecting TPs from the financial tool's time series, in the context of dynamic programming (DP) and then solves it optimally through a recursive procedure.Findings: Numerical results obtained from the application of the proposed model to four companies listed on the Tehran Stock Exchange indicate that the proposed model can detect the optimal financial TPs.Originality/Value: Originality in research mean what you are doing is from your own perspective although you may draw arguments from other research work to back up your arguments.
Multi-Attribute Decision Making
Mahsima Rasi; Hossein Mohammadi Dolat-Abadi
Abstract
Purpose: This research provides a framework for identifying the core competencies and consequently the competitive advantage of small and medium-sized manufacturing organizations in conditions of fuzzy uncertainty.Methodology: This research ranks of the core competencies using the group fuzzy TOPSIS ...
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Purpose: This research provides a framework for identifying the core competencies and consequently the competitive advantage of small and medium-sized manufacturing organizations in conditions of fuzzy uncertainty.Methodology: This research ranks of the core competencies using the group fuzzy TOPSIS method, which is a mathematical model.Findings: Research findings show that the core competencies of customer services and advertising are considered as a "competitive advantage" in small and medium-sized manufacturing organizations.Originality/Value: To extract the core competencies, the review conducted showed that the previous models ignore the resource-based condition. Moreover, only four main factors including the value creation, uniqueness, irreplaceability, and imitation are considered for screening the core competencies under competitive condition. Taking a different viewpoint, the framework proposed in this study not only encompass the resource based factors but also it covers the market base condition to identify the core competencies. Therefore, in addition to the four above-mentioned factors for screening core competencies, two more factors including the new market creation and scope of application are considered in this research. Also, as a novel application, a group fuzzy TOPSIS method has been developed to identify the core competencies under resource-based and market-based conditions.