Original Article
supply chain management analyzing/modelling
Javad Mohammadghasemi; esmaeil najafi; mohammad fallah; mohammad reza nabatchian
Abstract
In this paper, the modeling of a sustainable supply chain network of the electricity industry under uncertainty is discussed. The purpose of providing this supply chain network is to meet the customers' demand for solar panels in order to produce clean energy. In this model, important decisions were ...
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In this paper, the modeling of a sustainable supply chain network of the electricity industry under uncertainty is discussed. The purpose of providing this supply chain network is to meet the customers' demand for solar panels in order to produce clean energy. In this model, important decisions were made, including supplier selection, construction of production centers, optimal allocation of product flow and solar panel pricing. The results of the model showed that with increasing reliability in the network, the amount of net present value in the network has decreased and the amount of greenhouse gas emissions in the network has increased. Also, the analysis of the results showed that with the increase in the uncertainty rate in the network, the net present value and reliability in the network decreased and the amount of greenhouse gas emissions increased. On the other hand, further analysis on 15 numerical examples showed the high efficiency of two algorithms, MOALO and MOWOA, compared to the epsilon constraint method. Finally, the results of the statistical test also showed that there was no significant difference between the averages of the number of effective answers, the maximum spread and the metric distance between the two algorithms, and there was only a significant difference between the solving time of the two algorithms. The results of the presented solution methods show their high efficiency in solving the sustainable supply chain network model of the electricity industry.
Original Article
Non-linear Optimization
Seyed Hamzeh Mirzaei; Ali Ashrafi
Abstract
Purpose: One of the most effective methods for solving unconstrained optimization problems is the trust region method. The strategy of determining the radius of the trust region has a significant effect on the efficiency of this method. On the other hand, imposing the monotonocity condition will decrease ...
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Purpose: One of the most effective methods for solving unconstrained optimization problems is the trust region method. The strategy of determining the radius of the trust region has a significant effect on the efficiency of this method. On the other hand, imposing the monotonocity condition will decrease the convergence speed of this method. Therefore, improving and increasing the efficiency of this method is one of the most important issues and the attention of researchers.Methodology: Establishing a new adaptive trust region radius as well as combining the trust region method with a non-monotone strategy to avoid the adverse effects of monotonocity.Findings: A new adaptive trust region radius converged to zero is provided and then trust region combination is performed with a non-monotone strategy. Running the algorithm on a set of test functions shows that the new adaptive radius along with the non-monotone strategy used significantly improves the efficiency of the trust region method.Originality/Value: The presented non-monotone adaptive algorithm has a second-order convergence rate. In addition, it significantly reduces computational costs compared to traditional algorithms. On the other hand, the new adaptive radius avoids the ineffectiveness of the trust region close to the solution.
original-application paper
Strategic Planing
mohammadhossein kabgani; hamid shahbandarzadeh
Abstract
In a city, there are different sectors in operation and each sector also plays a role in the production of municipal waste, which draws attention to waste management methods. In the present study, a model to identify the factors affecting the production of waste in Bushehr has been explained.
Methodology: ...
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In a city, there are different sectors in operation and each sector also plays a role in the production of municipal waste, which draws attention to waste management methods. In the present study, a model to identify the factors affecting the production of waste in Bushehr has been explained.
Methodology: The main dimensions of the model are taken from the review of the theoretical literature in the field of urban waste management. Dynamic systems approach has also been used to identify urban waste management strategies, which is the main purpose of this study. In this research, we have tried to first identify the factors affecting the production of municipal waste and model it with the help of dynamic systems. Dynamic systems can include the complexity, nonlinearity, and cyclic feedback structures that are inherent in physical and non-physical systems. Therefore, they have the advantages of using the simulation method over the analysis methods. In the next step, the internal and external factors of the organization in the field of urban waste management and by referring to the SWOT analysis method, urban waste management strategies in Bushehr were performed.
Findings: The results of the SWOT method showed that the vulnerability threshold of urban waste management in Bushehr is very high and it is necessary to provide appropriate policies to address weaknesses and threats using strengths and opportunities. In the next step, Mikhailov's nonlinear method was used to rank the four strategies. The results of using this approach show that among SO strategies, the strategy of increasing awareness and changing citizens' attitudes towards proper waste management is in the first place. Among ST strategies, culturing for the use of recyclable containers weighing 0.51 is in the first place. Employing knowledgeable people for proper waste segregation and disposal among WT strategies, with a weight of 0.57 was ranked first, and finally the strategy of encouraging the private sector to invest with a weight equivalent to 0.43 among WO strategies Ranked first.
Originality/Value: The current research is innovative by focusing on combining fuzzy logic with dynamic systems modeling approach and Delphi method.
Original Article
Fuzzy Optimization
Mehrdad Rasoulzadeh; Seyyed Ahmad Edalatpanah; mohammad fallah; esmaeil najafi
Abstract
Goal: Increasing the wealth of shareholders is one of the most important goals of financial management. This issue is always intertwined with the two concepts of risk and return at the same time, so that hareholders always seek to increase portfolio return by controlling and minimizing risk, or seeking ...
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Goal: Increasing the wealth of shareholders is one of the most important goals of financial management. This issue is always intertwined with the two concepts of risk and return at the same time, so that hareholders always seek to increase portfolio return by controlling and minimizing risk, or seeking to reduce risk at a certain level of Returns are expected. For this purpose, investors mainly use the concepts of fundamental analysis and paying attention to the internal structure and financial performance of companies, or paying attention to the changes and price fluctuations of stocks in the market, or a combination of both methods.Research methodology: In this research, by combining the Markowitz model with fuzzy returns with the network data coverage analysis model, we will achieve a multi-objective model, which by considering the performance of companies based on some financial ratios and its effect on the stock market value, Also, price fluctuations will try to introduce stock portfolios in the best possible situations in terms of risk, return and efficiency of the stock portfolio. Finally, in order to use the model in selecting an optimal portfolio, 50 companies were selected from the active companies in the Tehran Stock Exchange, and the said model was implemented on them. Also, multi-objective algorithm with non-dominated sorting was used to solve the model.Findings: The results obtained from the implementation of the model on 50 companies active in the stock exchange show that the use of the proposed model is better than the use of any of Markobetz's models or network data coverage analysis alone, and also the ratio The non-network model provides investors with better results in terms of returns, risk and efficiency.
Original Article
supply chain management analyzing/modelling
samaneh rash; Mostafa Ebrahimpour Azbari; Mohammad Rahim Ramazanian
Abstract
Purpose: Commercial and industrial organizations around the world are under severe threat of instability. Unsustainability issues arise because of environmental disturbances such as climate change, global warming, resource scarcity, and ecological degradation. Circular Supply Chain (CSC) has gained momentum ...
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Purpose: Commercial and industrial organizations around the world are under severe threat of instability. Unsustainability issues arise because of environmental disturbances such as climate change, global warming, resource scarcity, and ecological degradation. Circular Supply Chain (CSC) has gained momentum in recent years and serves as one of the most sustainable and innovative approaches to the manufacturing industry. Adoption of the CSC increases the social, economic, and environmental aspects of the production system and the supply chain. However, researchers have conducted significantly less research on identifying and exploring the multiple challenges to implementing CSC in developing countries. Therefore, this research investigates and evaluates the challenges of CSC implementation in the production sector. We have identified 29 CSC challenges in the literature review.
Methodology: The research proposes the Pythagorean Fuzzy SWARA (PF-SWARA) technique. This technique is used to prioritize CSC adoption challenges based on their relative importance. We used the proposed method in the pharmaceutical industry of the Gilan Province.
Findings: We prioritize the criteria of Strategic Challenges (SCs) and operational and environmental challenges.
Originality/Value: This research result acts as a stepping stone for industrial practitioners to adopt CSC efficiently and effectively.
Original Article
Mathematical Optimization Models
Ali Abdi; Seyed Hadi Nasseri
Abstract
Purpose: One of the fundamental problems in the field of supply chain management is the problem of supply chain design. In this problem, the goal is to determine the location for establishing a number of facilities in different geographical areas to cover the demands of customers.
Methodology: In this ...
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Purpose: One of the fundamental problems in the field of supply chain management is the problem of supply chain design. In this problem, the goal is to determine the location for establishing a number of facilities in different geographical areas to cover the demands of customers.
Methodology: In this problem, the static and dynamic network is considered. Suppose the network is static, with the help of the iterated local search algorithm. In that case, the number and location of distribution centers are determined, and customers are assigned to each distribution center. If the network is dynamic, after determining the initial number and location of distribution centers and assigning customers to distribution centers, events related to network dynamics, such as customer decrease, customer increase, and variable size of demands, are investigated by customers. In addition, our proposed method considers the failure modes of network components. Also, the ability to survive the network can be seen in both network modes.
Findings: The results obtained from the experiments were analyzed in terms of evaluation criteria. The results of the experiments show the superiority of the proposed method compared to the CLSC and TSCFL methods.
Originality/Value: By studying the related works in the past in locating facilities in the supply chain network, attention to the design of a multi-level supply chain and the problem of finding facilities has yet to be considered. In addition, facility dynamics and network survivability are not considered at the time of failure. Therefore, in this research, we have tried to reduce the cost by choosing the appropriate location of facilities and assigning customers to each of these facilities. Also, we will design the network so that it can be in a stable state and continue to operate when a network failure occurs.
original-application paper
supply chain management analyzing/modelling
Behzad Masoomi; Hassanali Aghajani; Ahmad Jafarnejad; mohammadmehdi movahedi
Abstract
Purpose: The aim of this research is to optimize humanitarian logistics to increase coordination between actors in the phase during and after the disaster and aims to minimize the cost of relief, minimize the time of relief and minimize the cost of rebuilding infrastructure and housing for the affected ...
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Purpose: The aim of this research is to optimize humanitarian logistics to increase coordination between actors in the phase during and after the disaster and aims to minimize the cost of relief, minimize the time of relief and minimize the cost of rebuilding infrastructure and housing for the affected people.Methodology: This research is a part of developmental research in terms of the research directions types ; Because it is trying to expand the existing models in the design of the humanitarian logistics network and consider the optimization of two phases during and post-disaster. The proposed model of this research has been solved using multi-objective genetic algorithm and multi-objective particle swarm.Findings: The implementation of this study will lead to a reduction in the costs of locating, routing and reconstruction in the humanitarian supply chain, as well as reducing the time of providing aid to the affected people and increasing their satisfaction. It is also possible to reduce the inventory of relief products with the help of this issue. Appropriate planning in humanitarian logistics processes, especially in the coordination phase of reconstruction, will be done according to the limited budget of governments and the appropriate use of resources.Originality/Value: One of the innovations of this study is reducing the cost of reconstruction after an earthquake. Several studies were conducted in order to recover from the disaster. Over the past two decades, response phase relief operations have been the focus of a significant number of researchers. However, the issue of post-disaster recovery and reconstruction programs has not been sufficiently discussed in scientific and practical forums.
review paper
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.
Original Article
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.
Original Article
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.
Original Article
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.
Original Article
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.
Original Article
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.
Original Article
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.
original-application paper
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.
Original Article
Data Envelopment Analyses
Hosseinali Heydarzadeh; Fraydoon Rahnamay Roodposhti; Alireza Rashidi Komijan; 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.
Original Article
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.
original-application paper
Mathematical Optimization Models
Fatemeh nikkhoo; Ali Husseinzadeh Kashan; ehsan nikbakhsh; bakhtiar ostadi
Abstract
Purpose: The order picking problem is very important as one of the logistics activities of the warehouse. This problem is defined as collecting orders from different warehouse locations to respond to customers' orders in the shortest possible time. The purpose of this paper is to provide a multi-objective ...
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Purpose: The order picking problem is very important as one of the logistics activities of the warehouse. This problem is defined as collecting orders from different warehouse locations to respond to customers' orders in the shortest possible time. The purpose of this paper is to provide a multi-objective mathematical programming model for integrating the decisions of batching, routing, scheduling of pickers with the problem of packaging in multi-warehouse environment. The objective functions include minimization of the delivery times and total order picking costs.
Methodology: In this research, first by reviewing the literature in the field of order picking, the research gaps of the problem have been identified. Then, taking into account the main constraints of the problem, a multi-objective mathematical model has been formulated for the multi-warehouse order picking problem. To solve the problem, the classic Benders decomposition algorithm and the accelerated Benders decomposition algorithm have been used. To validate and applicability of the proposed model, the data related to the warehouses of a company producing sanitary products in Iran was used as a case study and its results were reported in the article.
Findings: The results of the proposed model indicate that CPLEX is able to solve these problems up to small sizes in an acceptable time. Also, the numerical results show the performance of the Benders decomposition algorithm and the accelerated Benders algorithm as suitable alternatives for solving the model in the large-sized problems. The calculation results obtained from the implementation of the solution methods for the proposed model showed that in terms of the number of iterations and the calculation time, the accelerated Benders algorithm had better results than the classic Benders algorithm.
Originality/Value: In this research, for the first time, the order picking problem with considerations of the integrity of operational decisions has been formulated in the form of a multi-objective mathematical model for a multi-warehouse environment. In this article regarding the solution method, exact solution approaches have been used for the first time considering the structure of the problem. The computation results show that the proposed algorithms are efficient and suitable methods for problem solving.
Original Article
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.
Original Article
meta-heuristic algorithms
Hossein Nikoo; Jamal Barzgari khanagha; Hamid Reza Mirzaei
Abstract
Purpose: Pair formation is an important step in pair trading that has only been examined manually or through numerical instructions. These methods fail in the multivariate mode and do not consider conflicting goals in the problem structure. In this research, a method is presented to create multivariate ...
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Purpose: Pair formation is an important step in pair trading that has only been examined manually or through numerical instructions. These methods fail in the multivariate mode and do not consider conflicting goals in the problem structure. In this research, a method is presented to create multivariate pair combinations by considering contradictory multiple goals in stock pair trading.
Methodology: In this study, the statistical sample is limited to the top 30 companies listed on the Tehran Stock Exchange due to the need for high-frequency transactions. The problem is developed in the form of a mixed integer programming model (MIP), and due to non-convex constraints and exponential solution space, a multi-objective genetic algorithm is used to obtain multivariate pair combinations. To achieve multiple goals, the developed type of genetic algorithm, namely, The Chaotic Non-dominated Sorting Genetic Algorithm (CNSGA-II), was used. In this method, chaos theory is used to create the initial population of the genetic algorithm in order to obtain appropriate and high-precision solutions.
Findings: The results showed that the use of chaos theory could increase the degree of convergence in evolutionary algorithms. In addition, these results indicate the superiority of the multi-objective pair trading strategy based on the distance approach over the traditional single-objective model.
Originality/Value: In order to optimize pair trading, the Non-dominated Sorting Genetic Algorithm was used. Also, the initial population of individuals was created in a multi-objective genetic algorithm based on chaos theory.
Original Article
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.
Original Article
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.
Original Article
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.