Data Envelopment Analyses
Zeynab Latifi; Neda Pouyan
Abstract
Purpose: Data Envelopment Analysis, one of the keys subfields in mathematical planning, has found a prominent role in evaluating the efficiency of decision making units in various fields. Methodology: In this research, after analysis and initial processing, based on studies, a parametric and efficient ...
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Purpose: Data Envelopment Analysis, one of the keys subfields in mathematical planning, has found a prominent role in evaluating the efficiency of decision making units in various fields. Methodology: In this research, after analysis and initial processing, based on studies, a parametric and efficient method for ranking intuitionistic fuzzy numbers is selected and proposed. The correctness of the performance of the selected method is obvious due to its formulation in linear structures. The developed model of data envelopment analysis, its mathematical formulation by CCR and IO-BCC methods are expressed in terms of governing the model structure and its implementation approach. A case study is presented to determine the factors affecting safety performance using the model. Based on previous theoretical studies and opinions of experts in the field of safety, the most important influencing factors (work pressure and perception of the supervisors' safety as inputs) and (the rate of physical and mental injuries and unsafe accidents as outputs) were selected. In addition to ranking the units, sensitivity analysis was performed in CCR and IO-BCC methods to rank the specified indicators in the inputs and outputs, and the results have been compared.Findings: The results of the data envelopment analysis model with intuitionistic fuzzy data showed that with increasing k, the number of efficient units increases. On the other hand, in CCR and IO-BCC methods, the lowest and highest efficiencies belong to the pessimistic view (k = 0) and the balanced view (k = 0.5), respectively. Sensitivity analysis also showed that, in CCR and IO-BCC methods, the work pressure is the most safety factor affecting the efficiency results.Originality/Value: Using a Data Envelopment Analysis model with intuitionistic fuzzy data to evaluate the performance of construction sites from a safety perspective can provide significantly better results. Because in the real world, there is uncertainty, and intuitionistic fuzzy data, due to the concept of belonging, non-belonging, and suspicion in the view of decision-makers simultaneously and in data reporting, is of particular importance.
Multi-Attribute Decision Making
Mehdi Ajalli; Nima Saberifard; Babak Zinati
Abstract
Purpose: Performance measurement in humanitarian logistics is considered as one of the basic elements of successful humanitarian operations at operational, tactical and strategic levels. The main purpose of this research is to identify and to extract key performance indicators in humanitarian logistics, ...
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Purpose: Performance measurement in humanitarian logistics is considered as one of the basic elements of successful humanitarian operations at operational, tactical and strategic levels. The main purpose of this research is to identify and to extract key performance indicators in humanitarian logistics, evaluating the indicators and explaining the relationship between them using path analysis approach and decision-making techniques of Fuzzy DEMATEL and SWARA and outline future research opportunities to measure performance in humanitarian logistics.Methodology: Performance measurement in humanitarian logistics is considered as one of the basic elements of successful humanitarian operations at operational, tactical and strategic levels. The main purpose of this research is to identify and to extract key performance indicators in humanitarian logistics, evaluating the indicators and explaining the relationship between them using path analysis approach and decision-making techniques of Fuzzy DEMATEL and SWARA and outline future research opportunities to measure performance in humanitarian logistics.Findings: The final finding of relationship analysis showed that "donation to delivery time" is the most influential indicator in terms of influencing other indicators. Finally, considering the sensitivity of ranking these indicators in terms of importance, the opinions of 20 experts and decision-making techniques SWARA used. The final output of this technique indicates the extraction of the fourth functional index i.e. "evaluation accuracy includes: speed and accuracy of committed donation and relief items delivered to stakeholders and how to assess the needs of stakeholders by employees" with the highest weight in the first rank as the most important functional indicator of humanitarian logistics and the second functional index i.e. "donation time includes "The delivery time of relief items in the country of destination after a donation and the collective remembrance of the donation" is important in the last rank.Originality/Value: In this study, performance indicators in humanitarian logistics were evaluated and ranked using a combined approach of path analysis and decision-making techniques (fuzzy DEMATEL and SWARA) and based on the research results, executive and research proposals were presented.
Mehdi Shams; Gholamreza Hesamian
Abstract
In this paper, the Wilcoxon ranked-sum test is generalized to the fuzzy environment based on a sample of fuzzy random variables. In the proposed approach, first by remembering the concept of induced fuzzy random variable from a family of distributions with fuzzy parameter, the fuzzy median of the population ...
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In this paper, the Wilcoxon ranked-sum test is generalized to the fuzzy environment based on a sample of fuzzy random variables. In the proposed approach, first by remembering the concept of induced fuzzy random variable from a family of distributions with fuzzy parameter, the fuzzy median of the population and the fuzzy median of a sample of fuzzy random variables are generalized to the fuzzy environment. The large sample property of a sequence of fuzzy sample mean is then investigated based on a popular fuzzy distance. Then a new method for testing fuzzy hypotheses for fuzzy median of a population is extended based on a criterion of belonging of a fuzzy set to the conventional critical region. For this purpose, the fuzzy Wilcoxon test statistic is first defined based on the fuzzy observations. Finally, at a given level of exact significance, a fuzzy test is proposed to test the fuzzy hypotheses of fuzzy median. The proposed method is finally illustrated with a practical example. The proposed approach is compared with other existing methods and the differences are examined.
Location Modeling
Alireza Roshani; Mohammad Reza Gholamian; Mahsa Arabi
Abstract
Purpose: Due to the increasing complexity of uncertainty and its impact on the supply chain network, many researchers have resorted to coping approaches with data uncertainty. In addition, the occurrence of any disruption in the supply chain networks can cause irreparable damage. Therefore, adopting ...
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Purpose: Due to the increasing complexity of uncertainty and its impact on the supply chain network, many researchers have resorted to coping approaches with data uncertainty. In addition, the occurrence of any disruption in the supply chain networks can cause irreparable damage. Therefore, adopting appropriate strategies to increase the level of the supply chain network resilience toward any disruptive events seem to be necessary.Methodology: In this paper, a multi-objective, multi-period, and scenario-based mathematical model is presented in which objective functions of delivery time and total network cost are minimized, and to increase network resilience, non-resilience measures are also minimized. Furthermore, a Two-Stage Stochastic Programming (TSSP) approach has been utilized to overcome the uncertain nature of the input parameters. Goal programming has also been used to transform the model into a single-objective one.Findings: In order to prove the model's applicability, the real-world data of a case study of Mashhad has been implemented. Eventually, according to the validation and sensitivity analysis results, the proposed uncertain model has clear superiority over the deterministic model.Originality/Value: This paper presents a multi-objective linear mathematical model for designing the Pharmaceutical Supply Chain (PSC) network under the COVID-19 situation. Two indicators of time and resilience as optimization tools have been considered simultaneously.
Multi-Attribute Decision Making
Seyyed Ahmad Edalatpanah
Abstract
Purpose: Designing an appropriate model/approach for decision-making (incredibly strategic decisions) in a complex and uncertain environment has always been one of the researchers' goals. This study proposes a method that can consider the above dimensions and provide a suitable answer to the challenge ...
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Purpose: Designing an appropriate model/approach for decision-making (incredibly strategic decisions) in a complex and uncertain environment has always been one of the researchers' goals. This study proposes a method that can consider the above dimensions and provide a suitable answer to the challenge of choosing the best option in the Matrix Approach to Robustness Analysis.Methodology: In this research, the superior option is identified by converting the matrix elements of the robustness analysis into hesitant fuzzy elements and using the score function.Findings: Implementation of the proposed approach in four different problems that in previous studies faced with the challenge of choosing the best option showed that a more appropriate answer could be achieved using hesitant fuzzy elements.Originality/Value: Developing the matrix approach to robustness analysis to solve the problem of choosing a strategy regarding equal stability of options.
Game Theory
Hamed Jafari
Abstract
Purpose: The purpose of this paper is to consider products such as disposable tableware produced from plastic waste. In this setting, plastic waste is collected, recycled, and reused. In this research, a supply chain including waste depot, recycler, and manufacturer is considered in which plastic waste ...
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Purpose: The purpose of this paper is to consider products such as disposable tableware produced from plastic waste. In this setting, plastic waste is collected, recycled, and reused. In this research, a supply chain including waste depot, recycler, and manufacturer is considered in which plastic waste is reused in order to manufacture a product. Under this supply chain, the waste depot collects non-recycled plastic waste and the recycler recycles it. Then, the manufacturer uses recycled plastic waste to produce final product and meet customer demand. In this structure, the waste depot, recycler, and manufacturer set the price of non-recycled plastic waste, the price of recycled plastic waste, and the price of final product, respectively.Methodology: The game theory is used to make the decisions under the considered supply chain. It is assumed that the decision power of the manufacturer is more than of the waste depot and recycler. In this setting, Stackelberg game-theoretic model is established in order to specify the prices adopted by the members.Findings: Results indicate that decision powers of the waste depot and recycler have no effect on the price and demand of final product. The profits allocated to the manufacturer are the same when decision powers of the waste depot and recycler are different. Moreover, more the price elasticity of the demand for final product leads to lower profits for the members.Originality/Value: Using plastic waste is an effective approach to sustain environment and reduce pollution. In this research, plastic waste is used to produce products such as disposable tableware in a supply chain including manufacturer, recycler and waste depot. The game theory approach is also used to make decisions. To our knowledge, the idea of applying the game theory to use plastic waste in production of products under the considered supply chain has been raised for the first time in the literature.
Forecasting Models/ Time Series
davood darvishi; Mostafa Nori joybari; parvin babaei
Abstract
Purpose: Covid-19 virus is a major threat to the health and safety of people around the world. One of the key components in dealing with this global threat is rapid and timely decision-making to control the epidemic of the disease, so predicting the future trend of this disease in the world, including ...
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Purpose: Covid-19 virus is a major threat to the health and safety of people around the world. One of the key components in dealing with this global threat is rapid and timely decision-making to control the epidemic of the disease, so predicting the future trend of this disease in the world, including predicting deaths, can be useful for policy-making, management and control of its prevalence. Therefore, the mortality rate caused by this virus has been predicted with grey models in the world.Methodology: This study examines the process of predicting mortality rates in the world using the theory of grey systems models. Research data were collected from the World Health Organization website and predicted the number of deaths in the world on a monthly basis by five methods: GM (1, 1), Verhulst Grey, DGM (1, 1), NGBM (1, 1) and FNGBM(1, 1). In order to evaluate the error of the models, the common error evaluation criteria MAE, RMSE and MAPE were used.Findings: By evaluating the model error, the prediction of the F-NGBM model (1, 1) in the category of excellent models, the prediction values of the GreyVerhulst model are in the category of acceptable predictions and the rest of the models are in the category of good predictions. Also, the F-NGBM (1, 1) model with MAE, RMSE and MAPE error values of 26989.54, 21533.94 and 7.21, respectively, is the most suitable model compared to the other methods. An estimated 250,958 deaths are estimated by the F-NGBM (1.1) model by the end of 2021, which may be the most appropriate value among forecasting methods.Originality/Value: Due to the lack of historical data and also a lot of uncertainty in the available data, it is necessary to use approaches to dealing with uncertainty such as the grey system theory in predicting the mortality rate of this disease. Various grey predictions estimate the mortality rate, which requires relatively less data than existing methods, and the model error is much lower. The study also looked at the worldwide mortality rate and will be more comprehensive on integrated global action.
Robust optimization
Amin Ghaseminejad; Mohammad Fallah; Hamed Kazemipoor
Abstract
Purpose: The present paper deals with modeling and solving a multi-objective problem of robust facility layout problem under uncertainty with NSGA-II, MOPSO and MOGWO algorithms. Since the problem of facility layout is NP-Hard, the need to use meta-algorithms by providing a suitable chromosome to achieve ...
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Purpose: The present paper deals with modeling and solving a multi-objective problem of robust facility layout problem under uncertainty with NSGA-II, MOPSO and MOGWO algorithms. Since the problem of facility layout is NP-Hard, the need to use meta-algorithms by providing a suitable chromosome to achieve near-optimal solutions has been investigated in this article. The issue under consideration in this article includes several departments that are based on 5 different aspects (minimizing the flow time between departments, maximizing the number of equipment and facilities, minimizing the distance traveled to access firefighting equipment, minimizing the distance to access optimal climatic conditions and maximization of noisy departments from each other) should be arranged in different parts of the hall. In order to achieve the above objective functions at the same time, assigning departments to each section, equipping each section with different equipments and arranging the departments together are among the main objectives of the article.Methodology: In this paper, GA, PSO and GWO single-objective meta-heuristic algorithms and NSGA-II, MOPSO and MOGWO multi-objective meta-heuristic algorithms have been used to solve the problem.Findings: Computational results show that GA, PSO and GWO single-objective algorithms have high efficiency in achieving the optimal value of the objective function in a much shorter time, and their multi-objective methods show the high efficiency of the NSGA-II algorithm in achieving the average value of the objective function. First, second and fifth; the MOPSO algorithm has the highest expansion and metric distance in achieving the average number of efficient answers and computational time, and finally the MOGWO algorithm in obtaining the average value of the third and fourth objective functions. Statistical comparisons also showed a significant difference between the means of computational time. To evaluate and rank the algorithms, the TOPSIS method is used and the results show the high efficiency of the MOGWO algorithm in solving the model.Originality/Value: In this paper, a new model of the multi-objective robust facility layout problem under uncertainty conditions is modeled with respect to health and environmental safety aspects.
simulation techniques and expert systems
Seyedeh Raahil Mousavi; Mohammad Mehdi Sepehri; Esmaeil Najafi
Abstract
Purpose: High efficiency in the operating room may significantly improve the overall performance of the hospital and the service quality provided to patients. The operating room is the de facto financial hub of the hospital and maximizing its efficiency may lead to considerable improvements. To this ...
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Purpose: High efficiency in the operating room may significantly improve the overall performance of the hospital and the service quality provided to patients. The operating room is the de facto financial hub of the hospital and maximizing its efficiency may lead to considerable improvements. To this end, we seek ways of accelerating the patient flow in order to save time and cost in healthcare facilities.Methodology: In this study, we use agent-based simulation to simulate patient care in the operating room. After performing the required validations, a number of improvement scenarios were developed and evaluated.Findings: A hybrid scenario including modifications to the referral time of the patient by the surgeon, transfer time of the surgical set and supplies to the operating room, and the timing of anesthesia proved to have the most positive impact on the criteria i.e. activities, reducing the average Length of Stay (LOS) by 9.69 minutes. The second-most effective scenario involved modifying the referral time of the patient by the surgeon, reduced the LOS by 7.31 minutes.Originality/Value: Through this research, it became apparent that minimizing the patients' LOS improves the efficiency of the operating room as it helps reduce the overall idle time and increases the number of operations carried out in each shift. Making time even for one additional operation per day significantly increases the operating room income. Moreover, a shorter LOS means less fatigue for the medical staff and reduces the total cost of running the operating room by reducing the staff's overtime hours.
supply chain management analyzing/modelling
Shahram Mokhlesabadi; Mohsen Hashemi Gohar
Abstract
Purpose: The purpose of this article is to design a GSNCL optimization in the dairy industry of Damdaran using FGP model.Methodology: This article is applied in terms of purpose and in terms of data type and how to implement descriptive-survey research and dissertation modeling, with a FGP approach and ...
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Purpose: The purpose of this article is to design a GSNCL optimization in the dairy industry of Damdaran using FGP model.Methodology: This article is applied in terms of purpose and in terms of data type and how to implement descriptive-survey research and dissertation modeling, with a FGP approach and has optimized the GSNCL in Damdaran industry. The society and the statistical sample consisted of 15 experts in the dairy industry of Damdaran, who have at least 10 years of executive experience in these industries and evaluation of supply network, as well as academic professors specializing in the field of GSNCL.Findings: The results of modeling and solving the numerical model, the importance of the role of financial dimension and simultaneous consideration of the environmental, financial and social dimensions in the mathematical model to gain competitive advantage of the GSNCL. Also, cost parameters have a positive effect on the economic performance of the main supply chain program, but by examining these parameters in sensitivity analysis, it causes a decrease in production performance in social and environmental dimensions.Originality/Value: Knowledge-enhancing research from an applied point of view can provide important information for decision makers, senior managers of dairy industry in the country about optimizing the GSNCL and maintaining the environment. The innovation aspect of the present study is to design a four-objective model to minimize economic costs, emissions of pollutant gases throughout the living network, the amount of social damages, and maximize the total revenue generated from the sale of products during the supply network using FGP. Modeling of FGP problem in a multilevel, multi-round and multi-product supply network has been carried out with the aim of minimizing undesirable deviations of each of the four ideals from the desired level.
Multi-Attribute Decision Making
Ahmad Negravi; Omid Titidezh
Abstract
Purpose: This study seeks to assess the significant effects of blockchain, as a new decentralized technology, in waste reduction and performance improvement of Freight Transportation Management Systems (FTMS).Methodolog: The network analysis technique is used as one of the most valid multi-criteria decision-making ...
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Purpose: This study seeks to assess the significant effects of blockchain, as a new decentralized technology, in waste reduction and performance improvement of Freight Transportation Management Systems (FTMS).Methodolog: The network analysis technique is used as one of the most valid multi-criteria decision-making models. We developed this model in four levels with four main criteria of performance wastes (including cost, time, trust and security and safety), and fourteen sub-criteria, considering the blockchain technologies in four areas of digital infrastructure, visibility, transparency, and smart contracts.Findings: Findings indicate that each of these technologies, individually and collectively, has reduced the waste of road freight management systems. The digital infrastructure technology reduced time and cost waste by 46.44% and 53.56%, respectively. Visibility has reduced 23.99%, 22.30%, and 53.71% of the wastes of cost, time, and safety, respectively. The transparency technology has influenced time and trust and security by 22.63% and 77.37%, respectively, and smart contracts affected the two above waste categories by 88.81% and 11.19%, respectively. The most effective wastes were identified as transportation costs, control costs, transparency in providing information, control of product conditions, and driver monitoring.Originality/Value: This study identified the most crucial road freight transport wastes and made it possible to determine priorities in various areas of blockchain technologies for future investment to improve the FTMS performance, and the findings of this study might be a starting point for future studies in this context.
Data Envelopment Analyses
Parisa Nankali; Fatemeh Rakhshan; Mohammad Reza Alirezaee
Abstract
Purpose: Customer loyalty is significantly dependent on customer satisfaction with the services provided. Therefore, customer satisfaction in offline services such as e-banking, offline account opening, etc. can be considered as an effective competitive strategy, especially in the current situation due ...
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Purpose: Customer loyalty is significantly dependent on customer satisfaction with the services provided. Therefore, customer satisfaction in offline services such as e-banking, offline account opening, etc. can be considered as an effective competitive strategy, especially in the current situation due to the corona virus pandemic.Methodology: In this study, first, by considering the appropriate loyalty codes at the level of bank branches, we define the appropriate weight constraints of the type of confidence zone constraints of the first type and add them to the basic model of data envelopment analysis. The new size obtained from this mathematical model is due to the effect of loyalty constraints and will have more resolution than the basic model. The loyalty factor of each branch is then defined as the ratio of the size of the new model to the base model, which will be a number between zero and one. Then, the proposed model is implemented in a case study consisting of 195 branches of the Housing Bank and the results of the model are analyzed.Findings: The results show that the loyalty factor is directly related to the quality of in-person services and a new measure of efficiency is obtained to monitor customer loyalty.Originality/Value: The data envelopment analysis method can be a suitable technique to evaluate the role of non-personal bank services in the level of customer loyalty and can help banks to retain customers.
Data Envelopment Analyses
Ehsan Jamasb Ghalati; Mohammadreza Mozaffari; Kazem Etemad
Abstract
Purpose: This study was carried out to propose cost and revenue models for evaluating road and urban construction and development projects in Shiraz (Iran) using Data Envelopment Analysis (DEA) and DEA based ratio data, (DEA-R) techniques. Today, we are encountering controllable and uncontrollable data ...
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Purpose: This study was carried out to propose cost and revenue models for evaluating road and urban construction and development projects in Shiraz (Iran) using Data Envelopment Analysis (DEA) and DEA based ratio data, (DEA-R) techniques. Today, we are encountering controllable and uncontrollable data in some projects. In this research, cost and revenue efficiency models were proposed considering controllable and uncontrollable indicators.Methodology: In this research, cost and revenue efficiency model with controllable and uncontrollable indicators in DEA and DEA-R is presented, also by measuring cost and revenue efficiency with controllable and uncontrollable indicators to compare the results between these two models Been paid.Findings: By comparing the results between cost and revenue efficiency models with controllable and uncontrollable indicators in DEA and DEA-R, it was concluded that it is not possible to make a logical comparison between them. But the proposed models can be important in order to use the input to output ratios. In some decision-making units, similar behavior may be present in DEA and DEA-R, but it is not a criterion for general comparison.Originality/Value: In this paper, a model for measuring cost and revenue efficiency with controllable and uncontrollable indicators was presented, which can be an introduction to provide more models for measuring cost and revenue efficiency under real conditions.
Multi-Attribute Decision Making
Mojtaba Movahedi; Mahdi Homayounfar; Mehdi Fadaei; Mansour Soufi
Abstract
Purpose: Clustering algorithms are useful tools for understanding data structure and classifying them into different data sets. Due to the importance of using these algorithms in analyzing financial market data that have a high volume and scope, this study in order to select the best clustering algorithm ...
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Purpose: Clustering algorithms are useful tools for understanding data structure and classifying them into different data sets. Due to the importance of using these algorithms in analyzing financial market data that have a high volume and scope, this study in order to select the best clustering algorithm for clustering companies listed on the Tehran Stock Exchange in the field of finance from It has used different clustering algorithms and evaluated the validity of these algorithms and selected the best algorithm.Methodology: This research is applied in terms of purpose and descriptive in terms of implementation method and is of quantitative type (mathematical modeling). The statistical population of the research includes 403 companies listed on the Tehran Stock Exchange in 2019, whose performance has been evaluated based on four financial criteria.Findings: After clustering the surveyed companies by five clustering algorithms, namely K-means, EM, COBWEB, density-based algorithm and ward method, seven indicators RS, DB, Dun, SD, Purity, Entropy and Time were used to evaluate the algorithms. Finally, the total performance of the algorithms was analyzed based on TOPSIS, VICOR and DEA methods. Based on the results, K-means has a better performance in clustering based on the financial data sets.Originality/Value: Since no clustering algorithm can have the best performance in all measurements for each data set, this study uses a combination of multiple criteria to analyze data clustering algorithms related to the field of financial performance appraisal. Companies have provided suggestions and the results of this study have been used effectively for investors in the field of finance, which leads to the optimal choice of investment portfolio.
Pegah Farhangian; Hadi Mokhtari
Abstract
Purpose: The classic model of economic order quantity was introduced several decades ago to reduce inventory costs in companies and has since been widely used in various areas of inventory control. In recent years, researchers have developed various aspects of the EOQ model; Because the classic EOQ model ...
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Purpose: The classic model of economic order quantity was introduced several decades ago to reduce inventory costs in companies and has since been widely used in various areas of inventory control. In recent years, researchers have developed various aspects of the EOQ model; Because the classic EOQ model does not take into account many important parameters in the real world. The purpose of this paper is to develop a classic EOQ model in order to operationalize and realize the assumptions in the space of simultaneous orders with imperfect quality items.Methodology: In this research, a mathematical modeling is developed for the imperfect inventory system as well as the simultaneous ordering requirement. Finally, a numerical example is provided along with the analysis of the results.Findings: The results show that changing the screening rate can have a significant effect on reducing or increasing costs. This cost effect is due to the cost of maintaining items of poor quality until the end of the inspection period. The faster the screening operation and the faster the defective items are removed from the system, the lower the cost.Originality/Value: In classic models, it is assumed that items of appropriate quality are ordered. In fact, due to the unstable quality of the production process, improper transportation, corruption or other factors, the presence of defective items is inevitable. In the proposed EOQ inventory system, these items are separated by 100% inspection of the consignment, and then these isolated items are sold in a package at a discounted price. Also, in order to reduce the fixed costs of ordering and shipping, the policy of simultaneous ordering has been used for all product categories, which has a high efficiency in reducing costs.
Financial Marketing Strategies
Shahram Eshragh; Narges Delafrooz; Kambiz Shahroodi; Yalda Rahmati
Abstract
Purpose: By increasing knowledge about the role of the brand in the success of industrial markets, the attention of buyers and suppliers in the industrial market, understanding the major factors affecting the performance of the industrial brand becomes important. Today, the petrochemical industry has ...
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Purpose: By increasing knowledge about the role of the brand in the success of industrial markets, the attention of buyers and suppliers in the industrial market, understanding the major factors affecting the performance of the industrial brand becomes important. Today, the petrochemical industry has played an important role in non-oil exports. Therefore, companies related to the petrochemical industry can play an effective role in the economic development of the country by creating an industrial brand. The purpose of this research is to analyze the factors affecting brand performance in the petrochemical industry.Methodology: In this study, through literature study, interviews with industry-related experts and analysis of data obtained through data analysis of the foundation, the main criteria related to brand performance were identified and classified, and in the next step using Dimatel decision method, the causal network structure of the criteria and sub-criteria were examined.Findings: In the qualitative phase of the paradigm model of the research, 10 main criteria were identified, including brand equity, sales efficiency, innovation in response, company reputation, modeling, brand-based organizational capital, organizational competitive strategies, distribution, product quality, production and volume and finally using Dimatel decision making method, organizational competitive strategies were identified as the most influential factor.Originality/Value: In this article, while using the appropriate features of qualitative and quantitative methods, provided a deeper understanding of the key factors affecting the success of the petrochemical industry brand performance and by providing a new model provides better competitiveness in this industry
supply chain management analyzing/modelling
Reza Khlilzade; Parviz Saeidi; Arash Naderian; Iebrhim Abbasie
Abstract
Purpose: The aim of this study was to design the financial agility model of the supply chain process in companies.Methodology: The research method is descriptive and applied. In terms of orientation, it is fundamental and in terms of purpose, it is exploratory-qualitative. The research population ...
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Purpose: The aim of this study was to design the financial agility model of the supply chain process in companies.Methodology: The research method is descriptive and applied. In terms of orientation, it is fundamental and in terms of purpose, it is exploratory-qualitative. The research population included: academic and industrial experts and the sample was selected based on the snowball sampling method. Data collection instruments were semi-structured interviews with industrial managers and academic experts. In the data analysis, first, the codes and components of financial agility were extracted from the interviews and formulated in the form of a conceptual Grounded theory model.Findings: The core category was the financial agility, which was presented in three dimensions, and the causal, contextual, and intervening conditions, and strategies and results, were formulated and then, the final model was designed. Afterwards, the model was validated by using the Delphi model. According to the results of this study, the main categories of the developed model included intra-organizational, technological and human factors.Originality/Value: Therefore, based on the proposed model of this research can be the expected consequences of the financial agility model in business companies can be understood.
Financial Marketing Strategies
Yousef Babazadeh; Reza Babazadeh
Abstract
The Islamic Revolution in Iran, always seeking a real Islamic society, has been a community centred on justice, progress and spirituality. To achieve this goal, a great deal of programs and policies have been developed and implemented. The general policies of resilient economies are the continuation ...
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The Islamic Revolution in Iran, always seeking a real Islamic society, has been a community centred on justice, progress and spirituality. To achieve this goal, a great deal of programs and policies have been developed and implemented. The general policies of resilient economies are the continuation and completion of past policies to achieve these aspirations. The pattern of resistance in the context of sanctions and due to its problems in the last decade has been elaborated and presented, but the thinking of this model is a comprehensive vision with long-term and strategic policies that are not just about economic sanctions. The purpose of this paper is to create a conceptual framework in which the tasks of different domains are determined to realize the resistance economy. This research seeks to answer the question of how the individual program or strategic plan of organizations and institutions is designed to achieve the goal of realizing a resilient economy? In this regard, it has been attempted on the basis of the general policies of the resistance economy, the message of the Supreme Leader and the study of the statements of leadership over the past seven years as well as the articles presented in the subject literature; the nature, requirements, characteristics and framework governing this template have been clarified that can be applied to use them.
Management and operational budgeting
Reza Bandarian
Abstract
The deviation between the raw estimation of size, time, and cost of projects and the real amount of them after execution projects, will lead to several difficulties for contractors. This fact demonstrates an essential to apply scientific methods to increase the accuracy of the early estimations. There ...
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The deviation between the raw estimation of size, time, and cost of projects and the real amount of them after execution projects, will lead to several difficulties for contractors. This fact demonstrates an essential to apply scientific methods to increase the accuracy of the early estimations. There are several approaches to calculate the cost of projects and one of them is algorithmic modeling. This study developed an algorithmic cost model to estimate size, time, and cost of engineering services project by benchmarking from Constructive Cost Model (COCOMO), which is an empirical model for calculating the cost of the software. This model uses size and cost drivers to increase the accuracy of estimation. The developed model has been run for a case study and by historical data from previous projects validated.
Multi-Attribute Decision Making
Mojtaba Akbarian; Esmaeel Najafi
Abstract
The strategy is most resources for organizational long term improvement and if it don’t deployment successfully, this process is ineffective even if appropriate strategies are released. The most stage in strategic deployment is resource allocation for implementation of strategic initiatives. With ...
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The strategy is most resources for organizational long term improvement and if it don’t deployment successfully, this process is ineffective even if appropriate strategies are released. The most stage in strategic deployment is resource allocation for implementation of strategic initiatives. With regard to resource restriction in the deployment of strategy, the ranking of strategic objectives with cause and effect relationships in the strategy map is important . In this paper after drawing of strategy map with DEMATEL method and identifying cause and effect relations between strategic objectives as network relations, the weight of each criterion is defined with analytic network process, and strategic objectives in the National Iranian Oil Refining & Distribution Company are ranked and according to this ranking strategic initiative are assigned.
supply chain management analyzing/modelling
Amin Mahmudi; Fatemeh Mojibian; Afrooz Noory Sabet
Abstract
In today’s highly competitive business environment, which is known by characteristics of low profitability, high customer expectations for high-quality products and minimum waiting time, make companies efforts to transform constraints into opportunities for gaining competitive advantage by optimizing ...
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In today’s highly competitive business environment, which is known by characteristics of low profitability, high customer expectations for high-quality products and minimum waiting time, make companies efforts to transform constraints into opportunities for gaining competitive advantage by optimizing their business processes. In such a situation, appropriate supplier selection can play a key role in the efficiency and effectiveness of the organization and have a direct impact on reducing costs, profitability, and flexibility of a company. The purpose of this research is to provide a supplier selection model with simultaneous consideration of two sources of inventory control and pricing in the supply chain. To assess the validity and reliability of the model, the actual data of the Seven Diamond Industries Company including input materials (Hot Roll) and products (galvanized sheets) have been used. The proposed model is coded in the GAMS software and its results have been analyzed.
stochastic/Probabilistic/fuzzy/dynamic modeling
Pourya Abbasi; Reza Radfar; Abbas Toloei Eshlaghi; Nazanin Pilehvari Salmasi
Abstract
Purpose: The present research seeks to identify the structure, how they interact and examine the factors that show the openness of the boundaries of the ecosystem of open R&D. For this purpose, the field of nanotechnology in Iran has been selected as the field of study.Methodology: In terms of research ...
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Purpose: The present research seeks to identify the structure, how they interact and examine the factors that show the openness of the boundaries of the ecosystem of open R&D. For this purpose, the field of nanotechnology in Iran has been selected as the field of study.Methodology: In terms of research method, this research is mixed and in terms of result, it is an application that has been done with the approach of Grandad theory, and research data were collected through library studies (a reference to existing documents and study of previous research), open interviews, and three semi-structured questionnaires.The statistical population is selected through a judgment-targeted method.7 academic experts (professors of R&D policies), 4 entrepreneurs(nanoscale-certified firms), and 4 policymakers in the nanotechnology sector (National Nanotechnology Initiative) were interviewed.Analysis of qualitative data obtained from open interviews with experts in Atlas.ti software, analysis of interrelationships through the Fuzzy-DEMATEL method in Exell, and analysis of the best decision and ranking of effective criteria for Monitoring the openness of the research and development ecosystem is performed by network analysis based on Fuzzy-DEMATEL method (DANP) in SuperDecision software.Findings: The findings of this study show that the structure of the R&D ecosystem in Iran`s nanotechnology has ecosystemic dimensions which consist of Human resources, Infrastructure, Financial resources, Governance as well as performance dimensions which consist of commercialization, scientific works, and patents as IP. Another finding of this study is that the Performance dimension has the greatest impact on reopening the frontiers of R&D in Iran's nanotechnology and the commercialization criteria have the highest weight to monitor the R&D ecosystem.Originality/Value: In addition to enabling policymakers to evaluate and measure policies and decisions made over time, it also helps companies streamline their knowledge and technology resources to learn, collaborate, and transfer Manage foreign companies and vice versa.
supply chain management analyzing/modelling
elham kouchaki tajani; Armin Ghane Kanafi; Maryam Daneshmand-Mehr; Ali-Asghar HoseinZadeh
Abstract
Purpose: Designing a logistic network is a vital and strategic issue that provides the optimal platform for effective and useful management of supply chain. For this purpose, in this paper, a multi-echelon, multi-product, multi-period and multi-objective sustainable dual-channel closed-loop supply chain ...
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Purpose: Designing a logistic network is a vital and strategic issue that provides the optimal platform for effective and useful management of supply chain. For this purpose, in this paper, a multi-echelon, multi-product, multi-period and multi-objective sustainable dual-channel closed-loop supply chain network has been designed taking into account the technology of RFID. Simultaneously this model seeks to maximize the profits and social responsibility of the supply chain network while it minimizes the whole delay in delivery time and environmental pollution. Also, because definitive models are incapable of understanding the complexities of real-world applications, so this paper also addresses systemic and environmental uncertainties.Methodology: In this study, the scenario-based stochastic robust programming optimization technique is used to deal with the uncertainty of the parameters and to deal with the uncertainty of the parameters, and due to the multi-objective model and for validation and model exact solution in small dimensions of a new robust augmented ε‑constraint method (AUGMECON‑R) is used to achieve the best balance between the objectives. Also, since the problem is of np-hard class, two NSGA-II and MOPSO algorithms were used to solve the model in larger dimensions.Findings: The results show that this model has acceptable efficiency that due to the uncertainty of some parameters.Originality/Value: The proposed model includes mathematical formulas in a certain and robust state that allows the establishment of several complicated characteristics in the above text along with direct and indirect selling channels and repairing centers and secondary costumers create the new design of supply chain that can be supreme model for the managers and professionals with the wide application especially from strategic view.
Combinatorial Optimization
MohammadSaviz Asadilari; Fariborz Jolai; Reza Tavakkoli-Moghaddam; Jafar Razmi
Abstract
By increasing the use of container transportation, one of the existing problems is the constant capacity of container terminals due to problems, such as lengthy construction process, lack of budget and space to build new locations, as well as lack of manpower. Also, this constant capacity leads to problems ...
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By increasing the use of container transportation, one of the existing problems is the constant capacity of container terminals due to problems, such as lengthy construction process, lack of budget and space to build new locations, as well as lack of manpower. Also, this constant capacity leads to problems such as reduced trade relations, increased maintenance and warehousing costs, increased transportation costs, and increased loading and unloading times, as well as container allocation problems. To solve this problem without increasing the area of the terminal, this paper present a mathematical model to allocate containers that can be used not only to solve this problem, but also in other cases such as transportation and shipping used. Due to the size of problems used in this research, a heuristic algorithm, namely LOGIC algorithm is used. According to studies, carried out in the literature, this algorithm has not been used in relevant problems so far. Also, due to the development of the LOGIC algorithm in this paper, it can be used for other large-scale optimization problems. The development of the proposed algorithm can be improved to solve the layout problem of maritime containers with other real constraints.
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 (MIP) model, 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.