Data Envelopment Analyses
Mohammad Alimoradi; Seyed Mohammad Ali Khatami Firouzabadi,; Maghsoud Amiri; Iman Raeesi Vanani
Abstract
Evaluation of performance and productivity and the process of its changes over time is considered essential in the process of improvement in organizations, production, industrial and service units. Regarding the estimation of productivity and productivity changes over time, different models, methods, ...
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Evaluation of performance and productivity and the process of its changes over time is considered essential in the process of improvement in organizations, production, industrial and service units. Regarding the estimation of productivity and productivity changes over time, different models, methods, approaches and indicators have been extracted and presented in various studies, one of the most important, common and widely used of them is the Malmquist Productivity Index. On the other hand, during production processes, undesirable products and outputs are produced simultaneously with desirable products. Therefore, with the development and expansion of the Malmquist Productivity Index, an index called the Malmquist Luenberger was introduced, which took into account the undesirable outputs while seeking to reduce them, and at the same time aimed at expanding the desirable outputs. Therefore, the current research and review paper, based on the PRISMA methodology, with the aim of a structured and systematic analysis of articles and researches on this subject. This research is of a review type that is conducted through searching in domestic and foreign databases such as Academic Jihad Scientific Information, Scopus, Science Direct, Elsevier and Google Scholar in the period from 1980 to 2022 with the approach of selecting the most important, most valid and prominent papers and Internal and external scientific and applied research has been carried out. The results of the current research show the existing scientific gaps and future suggestions regarding productivity evaluation using the Malmquist/Malmquist Luenberger Productivity Index.
Multi-Attribute Decision Making
Ahmad Jafarnejad Chaghoshi; seyed mahdi rouhani poor; hannan Amoozad Mahdiraji; Mohammad Ehsanifar
Abstract
Purpose: product quality includes three variables: design, conformance and use. Measuring the quality of products with respect to all three quality variables is one of the important challenges of the country. Therefore, the present study was an attempt to figure out how quality factors are related to ...
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Purpose: product quality includes three variables: design, conformance and use. Measuring the quality of products with respect to all three quality variables is one of the important challenges of the country. Therefore, the present study was an attempt to figure out how quality factors are related to each other and to determine the relative weight of these factors and to provide a product quality measurement model using hesitant fuzzy linguistic terms.
Methodology: The present study falls into the category of applied studies in terms of objective and can be recognized as a quantitative study in terms of methodology. The population of the study incorporates academic experts and university-industry experts. Sample size (n=10) was determined using the purposeful and snowball sampling method. Due to the uncertainty of experts' in determining the mutual impact of product quality factors, the DEMATEL technique was combined with hesitant fuzzy logic, the resulting technique was then integrated with the network analysis process (DANP), and the final model was extracted. Thanks to this procedure, the present study can be deemed innovative.
Findings: The cause and effect relationships between the main factors of product quality were identified and extracted using DEMATEL technique. Then, taking into account the intensity of the mutual impact of quality factors on each other and using the DNAP technique, the product quality factors were ranked in three dimensions: design quality, conformance and use. According to the findings, management factors and resources (employees-infrastructure-environment) were identified as causal factors that affect other factors. On the other hand, the DANP output showed that "design quality" is the most important factor in product quality. so, with the relative weights of the factors, the product quality measurement model was obtained.
Originality/ value: Researchers and industrial managers at the national level will be able to identify the relationship between quality factors and use this model to measure product quality or the quality rate of goods according to relative weight of each factor.
Optimization in science and engineering
zohre kiapasha; ali salmasnia
Abstract
Purpose: Cloud manufacturing is a service-oriented production model that centralizes production resources available in different geographical locations to respond to specific customer needs. One of the main issues in cloud manufacturing systems is the proper allocation of sub-tasks to enterprises and ...
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Purpose: Cloud manufacturing is a service-oriented production model that centralizes production resources available in different geographical locations to respond to specific customer needs. One of the main issues in cloud manufacturing systems is the proper allocation of sub-tasks to enterprises and their optimal scheduling. Most studies in the literature assume that all tasks have only one type of structure, although it is possible to have tasks with different structures in one order set. Furthermore, existing scheduling models in the cloud manufacturing literature tend to assume that all tasks are available at time zero and that the logistics time/cost among enterprises is negligible. Therefore, in this study, an optimization model with three objective functions of task completion time, the cost imposed on the cloud manufacturing system, and the quality of the selected services is developed in which to get closer to the real world, three features are included in it: 1) the possibility of tasks with two structures, series and parallel, 2) different arrival times of tasks in the cloud manufacturing system, and 3) time/cost of logistics between different enterprises.
Methodology: First, six examples with different numbers of tasks and subtasks are designed with both sequential and parallel structures. In order to accurately solve the proposed model and achieve the global optimum, the CPLEX solver is used in the GAMS software.
Findings: In order to verify the importance of the characteristics of the developed model, two comparative studies are carried out. In the first comparative study, the presented model is compared with a similar model in which it is assumed that all tasks are available at time zero. The second comparative study examines the effect of considering logistics time/costs between enterprises when allocating subtasks to services. The results of the comparative studies show the misleading level of the cloud manufacturing manager in the face of the reduced models.
Originality/Value: The output of this research is to present a model for the simultaneous scheduling of tasks with sequential and parallel structures, taking into account the different task arrival times and logistics in the cloud manufacturing system.
supply chain management analyzing/modelling
zeinab asadi; Hassanali Aghajani; mohammad valipourkhatir; Erfan Babaee Tirkolaee
Abstract
Purpose: The COVID-19 pandemic has led to a significant crisis in society’s health, industries, and businesses. In this regard, the medical devices industry has played an important role in crisis management and providing healthcare and has faced with several major challenges in supplying raw ...
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Purpose: The COVID-19 pandemic has led to a significant crisis in society’s health, industries, and businesses. In this regard, the medical devices industry has played an important role in crisis management and providing healthcare and has faced with several major challenges in supplying raw materials, production activities, and distribution activities due to the disruptions caused by the pandemic. One of the critically important issues in the medical devices supply chain is supplier selection. Hence, this research investigates the supplier selection problem considering the emerging concepts, which have dramatically attracted the attention of researchers after the COVID-19 pandemic, namely viability and Industry 5.0.
Methodology: In this study, a hybrid fuzzy decision-making approach is developed to investigate the viable supplier selection problem considering the Industry 5.0 dimensions. In this regard, in the first stage, according to the literature and experts, the main indicators of the research problem are extracted and then their weights are calculated using the fuzzy best-worst method. In the next stage, by employing the fuzzy VIKOR method, the feasible suppliers are evaluated. Also, to show the robustness and validation of the proposed approach, its results are compared with the traditional approaches.
Findings: In this study, a list of indicators, including six aspects and 34 criteria, is provided for the research problem based on its nature and their importance have been computed. Based on the outputs, the general metric is the most important aspect and the human-centricity metric is the least significant one. Also, the results show that in addition to the general criteria, such as cost and quality, other criteria such as reliability, technical capability, pollution control, risk reduction and service also play a significant role in the process of selecting suppliers and managers should pay special attention to these indicators in nowadays competitive marketplace.
Originality/Value: Reading the results of this research can help the Industrial and organizational managers to evaluate the potential suppliers of their companies based on the viability and Industry 5.0 dimensions, and select the best ones, which can significantly improve the performance and efficiency of their businesses.
Fuzzy Optimization
Malihe Niksirat; Majid Abdolrazzagh nezhad
Abstract
Purpose: In this paper, a Binary Fuzzy Linear Programming Problem (BFLPP) with fuzzy objective function and fuzzy constraints is considered. The purpose of this paper is to propose a new approach that solves the problem based on kerre’s adapted method that maintains the assumption of being fuzzy ...
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Purpose: In this paper, a Binary Fuzzy Linear Programming Problem (BFLPP) with fuzzy objective function and fuzzy constraints is considered. The purpose of this paper is to propose a new approach that solves the problem based on kerre’s adapted method that maintains the assumption of being fuzzy in the solving process. Therefore, the solution is more consistent with the conditions of uncertainty governing the problem.
Methodology: In this paper, a new fuzzy branch-and-bound approach based on Kerre's adapted method is proposed to solve the fuzzy binary integer programming problem. In each node of the branch-and-bound tree, the linear relaxation of the fuzzy problem is solved with a new fuzzy simplex method based on Kerre’s adapted method.
Findings: Numerical examples are presented to illustrate the proposed method step by step and the results are compared with other approaches that solve fuzzy binary integer programming problems.
Originality/Value: Unlike the available defuzzification procedures and fuzzy ranking functions in the literature of the research problem, the proposed approach considers the assumption of being fuzzy in the solution process and thus offers a more realistic solution.
Forecasting Models/ Time Series
Adel Gardoon; Nader Khedri; Ali Mahmoodi; Mehdi Basert
Abstract
Purpose: Financial statements are the main decision-making bases of capital market actors; which is affected by internal and external factors. Uncertainty in other markets is one of the most important factors affecting the financial statements of listed companies. As a result, the aim of the current ...
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Purpose: Financial statements are the main decision-making bases of capital market actors; which is affected by internal and external factors. Uncertainty in other markets is one of the most important factors affecting the financial statements of listed companies. As a result, the aim of the current research is to model the spillover of uncertainties of parallel markets on the types of profit management.Methodology: The present research is practical. The research period is a 10-year period with seasonal data between 2011 and 2021. VAR-MGARCH model has been used to investigate the spillover of uncertainties of parallel markets on the types of profit management.Findings: Based on the results of VECH, CCC, BEKK and DCC models to extract the uncertainty of the studied variables; VECH models had higher accuracy. Based on the results of multivariate GARCH models, the spillover effect between different markets was observed. As a result, the uncertainty of one market strengthens the uncertainty between other markets. Based on the results of vector autoregression model; Uncertainties of variables have a stronger effect on accrual profit management than actual profit management. The results of variance analysis show the fact that oil price uncertainty has the highest contribution in the interpretation of real profit management change and exchange rate uncertainty in the interpretation of accrual profit management change.Originality/Value: Uncertainties of parallel markets reinforce each other and increase the level of profit management in the investigated companies.
Bahman Norouzpour; mahmoud Moradi; Mohamad Rahim Ramezanian; Mostafa Ebrahimpour Azbari
Abstract
Purpose: In recent years, concepts such as the fifth generation university, the fifth generation of industry and society have been continuously raised among the researches. The success of the university in the fifth mission and formation of the fifth generation of industry and society requires considering ...
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Purpose: In recent years, concepts such as the fifth generation university, the fifth generation of industry and society have been continuously raised among the researches. The success of the university in the fifth mission and formation of the fifth generation of industry and society requires considering the fact that both university and industry are the main actors of knowledge and business ecosystems. Without considering the comportment of these actors in the context of ecosystems, it is not possible to form a proper communication process between these institutions. Therefore, the aim of the paper is to develop a conceptual model to explain the cooperation between knowledge and business ecosystems
Methodology: This research is interpretive from a philosophical point of view and inductive from the point of view of theory development. The research strategy is "Grounded Theory" which was used to present a conceptual model. The systematic procedure of Strauss and Corbin was used to create a suitable structure for better understanding and classification of data and findings. In order to check the validity of the data, two methods of Member Checking or Participant Feedback and reviewing by External Audit were used. Furthermore, in order to check the reliability of the research findings, the method of fixed index or Re-test Reliability was used.
Findings: The results show that in order to form cooperation between industry and university as the main actors of business and Knowledge ecosystems, 18 key and vital categories should be taken into consideration. A conceptual model is presented in order to describe the relationship between these categories.
Originality/Value: It can be claimed that despite the studies conducted in the field of cooperation between industry and university, a model for this cooperation has not been developed so far and only the challenges of this cooperation have been discussed or a series of concepts have been discussed. In this research, an attempt has been made to present such a model by taking into account theories such as ecotone and ambidextrous organization, and various aspects of this cooperation have been investigated.
Multi-Attribute Decision Making
Fatemeh Bahman; Alireza Shahraki; Sayyid Ali Banihashemi
Abstract
Purpose: Based on the uncertainty in the supply chains, one of the important issues for public health is to assess the resilience of drug supply chains. The purpose of the current research is to determine and weigh the effective criteria on the resilience of the supply chain and the ranking of drug distribution ...
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Purpose: Based on the uncertainty in the supply chains, one of the important issues for public health is to assess the resilience of drug supply chains. The purpose of the current research is to determine and weigh the effective criteria on the resilience of the supply chain and the ranking of drug distribution companies based on the criteria.
Methodology: The current research is a quantitative-qualitative and applied research. The statistical population was 83 people and the sample was 68 people based on Morgan's table with a margin of error of 5%, which were selected by simple random sampling. Data collection was implemented with field method, library studies, interviews and questionnaires. The questionnaire was approved by experts and its’ reliability with Cronbach's alpha coefficient of 0.965. The percentage of personal characteristics were calculated using SPSS-26 software. Due to linguistic uncertainty, the weighting of the criteria was done with the fuzzy SWARA decision-making method and the ranking of the options for more accurate evaluation was performed by the interval type-2 fuzzy CoCoSo method in Excel software.
Findings: The identified criteria in order of importance are knowledge management, agility, readiness and prediction, management method, supply chain design and structure, visibility and control, adaptability, collaboration, complementarity, innovation, complexity management, flexibility, uncertainty in the amount of changes, and integration. The top three drug distribution companies are DarouPakhsh, AdoraTeb, and Ferdous, respectively.
Originality/Value: The weighting of the criteria indicates which criteria have a greater impact on the resilience of the supply chain. Therefore, the company will be given a higher priority if it pays attention to criteria with higher weights.
Data Envelopment Analyses
Hosseinali Heydarzadeh; Fraydoon Rahnamay Roodposhti; Alireza Rashidi Komijan; Seyyed Esmaeil Najafi
Abstract
Purpose:This research aims to construct a portfolio based on risk-adjusted performance and distribution-based returns and determine the efficiency using the data envelopment analysis (DEA) approach. In this study, the role of return distribution in the efficiency of risky assets is also examined to form ...
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Purpose:This research aims to construct a portfolio based on risk-adjusted performance and distribution-based returns and determine the efficiency using the data envelopment analysis (DEA) approach. In this study, the role of return distribution in the efficiency of risky assets is also examined to form a diversified portfolio consisting of assets with varying degrees of performance.Methodology:In this study, the diversified portfolio's performance based on the risk-adjusted value and conditional risk-adjusted value obtained from the probability distributions of returns was compared with the minimum-variance Markowitz portfolio performance in terms of the Sharpe ratio. After estimating the maximum likelihood parameters of the model, the risk values for each stock were calculated based on the empirical return distribution, the Cauchy distribution, and the normal distribution. These risk values were then used in the data envelopment analysis to calculate the efficiency scores of each company.Findings:The diversified portfolio with stock performance degrees outperforms the minimum-variance Markowitz portfolio in terms of risk-adjusted and conditional risk-adjusted values. The probability distribution of returns leads to different results in calculating stock risk-adjusted value/conditional value, with the empirical return distribution and normal distribution providing a more desirable performance (in terms of the Sharpe ratio) compared to the Cauchy distribution and sample ratios.Originality/Value:In the literature, an efficient portfolio is usually formed by calculating asset weights in the stock basket so that the Sharpe ratio reaches its maximum value. In the current study, this hypothesis is challenged in favor of the proposed method, which estimates portfolio weights based on the efficiency of risky assets.
Strategic Planing
Zahra Joorbonyan; Ali Sorourkhah; Seyyed Ahmad Edalatpanah
Abstract
In a competitive environment , various ways to maintain, survive, or grow the organization are conceivable. Among these, marketing experts believe that customer loyalty is one of the most effective tools in facing this challenge. To achieve customer loyalty, various and diverse strategies have been mentioned ...
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In a competitive environment , various ways to maintain, survive, or grow the organization are conceivable. Among these, marketing experts believe that customer loyalty is one of the most effective tools in facing this challenge. To achieve customer loyalty, various and diverse strategies have been mentioned in the literature by researchers and experts, which organizations can use, depending on the conditions, one or a combination of them. In such circumstances, managers usually have several strategies at their disposal and must choose the most appropriate one(s) from among them. The present study aims to provide a combined approach for prioritizing customer loyalty strategies.
This research uses a matrix-based approach to robustness analysis, which can deal with both complexity and uncertainty. The proposed algorithm combines it with strategic planning tools (strategies derived from strategic objectives and SWOT analysis) for prioritizing and selecting strategies. The proposed approach was implemented in a case study on prioritizing customer loyalty strategies for a women's clothing boutique in Ramsar City. Available strategies, influential environmental variables, definitions of future scenarios, and the performance of strategies in different environmental conditions were determined based on the judgments of the problem owner.
The results showed that considering influential environmental variables (national currency value, market access and raw materials, lifestyle changes, investment security, government-private sector relations, and the speed of technological change), supplier selection, contractor selection, and attracting a sponsor have the highest priority strategies. Afterward, environmental advertising, collaborative production, and customer relationship management were placed in subsequent rankings. The outputs of the proposed approach indicate that considering the country's foreseeable future conditions, higher-priority strategies minimize environmental risks and their impact on the business.
The literature suggests that classical strategic planning approaches (QSPM) or multi-criteria decision-making approaches (MCDM) are used in most cases of such decision-making. Despite their capabilities and features, these approaches face challenges in dealing with variable and evolving conditions (future uncertainty). An alternative approach, robustness analysis, can consider alternative futures but cannot define available strategies. Based on this, combining the matrix approach to robustness analysis with classical strategic planning approaches will be a response to the above problem.
stochastic/Probabilistic/fuzzy/dynamic modeling
Seyed mahdi Ghanizadeh
Abstract
Purpose: The purpose of this research is to present a new hybrid method for evaluating and choosing the right human resources for the right position in the organization under conditions of uncertainty.
Methodology: In this research, the grey relationship analysis (GRA) method developed with positive ...
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Purpose: The purpose of this research is to present a new hybrid method for evaluating and choosing the right human resources for the right position in the organization under conditions of uncertainty.
Methodology: In this research, the grey relationship analysis (GRA) method developed with positive and negative ideal concepts is used to evaluate the employees and human resources of organizations and put the right person in the right position. Also, to evaluate the effective criteria in human resource evaluation, the best-worst method is used. Finally, the two presented methods are developed in the interval-valued fuzzy environment for facing uncertainty.
Findings: The proposed method was successfully applied to the problem of evaluating human resources in an environment of uncertainty. Also, according to the best-worst method, it was found that the knowledge and experience of the person are very important and have the most weight. Finally, using the developed GRA method, it was determined that among five candidates, person number 3 is suitable for managing systems and methods in the organization.
Originality/Value: In this research, the GRA method is improved based on positive and negative ideal concepts and developed in interval-valued fuzzy environment. Then, to weigh important criteria in the personnel evaluation process, the developed BWM method under interval-valued fuzzy environment is used. Interval-valued fuzzy sets provide more degrees of freedom for real-world uncertainty due to having interval membership degrees. Finally, the position of systems and methods manager, a new job in organizations, has been examined.
Optimization in science and engineering
Ali Sheykhani; Farshad Hosseinzadeh Lotfi; Arash Maghsoudi
Abstract
Worldwide, the rate of preterm births is increasing, so there will be significant health, development and economic problems. Premature birth is one of the leading causes of death and a significant cause for the loss of human potential among survivors around the world. Complications of preterm birth are ...
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Worldwide, the rate of preterm births is increasing, so there will be significant health, development and economic problems. Premature birth is one of the leading causes of death and a significant cause for the loss of human potential among survivors around the world. Complications of preterm birth are the single largest direct cause of neonatal death. Current methods for early detection of such labor are insufficient. One promising technique, recognized in monitoring uterine activity, is the use of advanced device learning algorithms and electrohistrography (EHG) induction. In this article, a learning machine is designed to diagnose different types of deliveries. Using deep learning algorithms, electrohistrographic signals have been used to detect preterm birth. The results were obtained using a data set that included 262 cases for women who had a preterm delivery and 38 cases for women who had a preterm delivery. Using the "cross" technique, 4 types of data sets were implemented in two ways, with training and without training. The results obtained in this study showed that the error on this set of data was one percent.
supply chain management analyzing/modelling
Masoud Rabbani; Maryam Hemmati; mohammadReza mehregan
Abstract
Purpose: One of the biggest challenges of the 21st century is meeting the needs of the growing world population. The supply chain of perishable goods, including food, dairy products, medicines, and blood products, have recently received attention due to their impact on human life. In this article, the ...
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Purpose: One of the biggest challenges of the 21st century is meeting the needs of the growing world population. The supply chain of perishable goods, including food, dairy products, medicines, and blood products, have recently received attention due to their impact on human life. In this article, the design of a sustainable supply chain network for perishable items has been discussed. To optimize this supply chain, a multi-objective mixed integer linear programming (MILP) model has been developed to formulate the problem. Fixed deterioration rate (expiration date) is considered.
Methodology: To perform the research calculations, GAMS software and the combined method of Bander's analysis and Lagrange coefficient were used, and based on the data, results were obtained, and the relative weight of the stability of the solution (ω) was equal to 0.5 and the relative weight of the stability of the model was ( ω) equal to 5000 has been developed to meet the proposed objectives. These comparisons show that the presented network was robust in all performance objectives.
Findings: The results obtained from the combined method regarding the three objective functions defined for the main model show this fact. The results of the first iteration provide us with better answers compared to the other iterations.
Originality/Value: This research can be considered as one of the first optimization paper that presented a multi-level and multi-product-multi-period supply chain with uncertainty in the parameters in the dairy and pharmaceutical industries and the environmental costs of production and transportation, and sustainable social costs such as reported accidents and incidents, job satisfaction, safety, reduction of dispatch time and lost working days simultaneously with the economic dimension in management-related decisions. Allocation combines location and routing.
supply chain management analyzing/modelling
Sajad Amirian; Maghsoud Amiri; Mohammad Taghi Taghavifard
Abstract
Purpose: In this research, a multi-product and multi-period closed-loop supply chain design problem with three objectives of profitability, social responsibility, and reliability under uncertain conditions has been considered.
Methodology: Triangular fuzzy numbers have been used for non-deterministic ...
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Purpose: In this research, a multi-product and multi-period closed-loop supply chain design problem with three objectives of profitability, social responsibility, and reliability under uncertain conditions has been considered.
Methodology: Triangular fuzzy numbers have been used for non-deterministic parameters and a robust probabilistic programming approach with Me scale has been used to deal with fuzzy constraints. The proposed approach eliminates the need for iterative consideration by decision-makers by providing unlimited choices from the optimism-pessimism spectrum. The mathematical model developed in this research is of mixed integer linear programming type, which is implemented in GAMS software to solve it and find Pareto optimal solutions.
Findings: The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the aluminum industry. The sensitivity analysis of the demand parameter showed that the proposed model achieved more economic profit, less social responsibility, and less reliability with increasing demand.
Originality/Value: The variability of the justified decision space in the Me criterion has helped to solve the supply chain network design problem more flexibly and closer to reality through the possibility of exchange between the objective function and the risk-taking level of the managers.
Mathematical Optimization Models
Javad Alikhani Koupaei; Mohammad Javad Ebadi; Majid Iran Pour
Abstract
This study aims to compare the performance of the First Carrier Wave Chaos Optimization (FCW) algorithm with other optimization methods to determine the appropriate shape parameter of radial basis functions (RBF) for solving partial differential equations (PDEs). The selection of the FCW method is based ...
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This study aims to compare the performance of the First Carrier Wave Chaos Optimization (FCW) algorithm with other optimization methods to determine the appropriate shape parameter of radial basis functions (RBF) for solving partial differential equations (PDEs). The selection of the FCW method is based on its simplicity and foundational characteristics among chaotic optimization algorithms. To achieve this goal, a two-stage process will be employed, in which the Kanza method, based on non-grid-based local techniques, is combined with the FCW method. In the first stage, the FCW algorithm is used to obtain the optimal shape parameter for the radial basis function, and then in the second step, the Kanza method is employed to estimate the root mean square (RMS) error for the approximate solutions. The numerical results derived from two partial differential equations, employing the PSO and FCW algorithms, reveal an approximate 95% conformity. This signifies the effectiveness and efficiency of this methodology in estimating appropriate shape parameters. It accentuates the pivotal role of chaos-based optimization algorithms as powerful tools in the effective resolution of partial differential equations.