فصلنامه مطالعات مدیریت صنعتی
پیاپی 63 (زمستان 1400)

The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development of aquaculture and recycling of returned goods in reverse logistics would significantly help with preserving water resources, as well as sustainable development. Therefore, government agencies and aquaculture industry beneficiaries are interested in reverse logistics. This study is focused on the optimization of a closed-loop supply chain of fish. To this end, a new bi-objective mathematical model is proposed that both minimizes total costs and maximizes fulfilling customers demand in uncertainty situation. Several well-known multi-objective meta-heuristic algorithms and a proposed hybrid meta-heuristic algorithm are applied to identify Pareto solutions. The solutions are then compared in terms of performance metrics. Also, the epsilon-constraint method and sensitivity analysis are used to validate the algorithms and evaluate the performance of the model. Lastly, the VIKOR method is used to select the superior method. To demonstrate the capability of the proposed model, a closed-loop supply chain of trout in northern Iran is investigated as a case study. The results show that the developed model could be effective in reducing the costs and increasing customer satisfaction.

Nowadays with increasing environmental pollution government's attention to the concept of the green supply chain has increased. The green supply chain produces a green product that is highly environmentally friendly. The purpose is to examine the impact of government intervention on competition between chains, the environment and social welfare. This article presents three different models. In the first model the two green and non-green supply chains are competing with each other and the government is not present. In the second model, the government creates a culture to use the green supply chain and in the third model, is taxing the non-green supply chain. The objective of government is social welfare. In both models of government intervention, the game is in the form of a Stackelberg. Backward analysis method is used to solve the model. This method is a backward inference process in problems with limited steps, with the aim of obtaining optimal action in each step. MATLAB and Maple software are used for mathematical calculations and obtaining decision variables. The results show that if the government intervenes in a cultural way, environmental damage will decrease. Another result is that the conditions for increasing social welfare in the state of culture are determined. It is also possible for the green supply chain to increase its price if certain relationships are established between the parameters. In the tax collection model, if the government aims to maximize social welfare, social welfare will increase under any circumstances compared to the absence of the government.

The oppressive sanctions of the superpowers in the supply of our country's military equipment, as well as the use of a significant number of helicopters with military and civilian applications (including transportation, rescue, agriculture, fire, crisis management, etc.), in the country, The importance of Iran Helicopter Support and Renovation Company (Panha) has doubled and the functional diversity of these helicopters has made it necessary for the company to move towards design and construction. Given the company's mission and existing constraints, including sanctions, effective supply chain management is a key factor in its success. Disruptions as a result of unexpected events are an integral part of the company's supply chain, and applying the supply chain resilience approach to deal with these unexpected events, rapid recovery and return to normal (before the event), as the only A company providing support and modernization services for helicopters in Iran is essential.The purpose of this research is to develop a supply chain resilience model for Panha Company. First, the supply chain resilience practices are identified, then, according to the necessity of the applicability of the final model, practices is categorized in the form of a two-dimensional matrix of importance - feasibility. Also, using fuzzy Delphi method, the most important practices and performance measures related to Penha Company were extracted. Finally, using interpretive structural modeling, a model is presented that shows the relationships between important and feasible practices of the company's supply chain resilience.

The purpose of this article is to develop a model of manufacturing flexibility in the food industry. The present research is a mixed qualitative and quantitative research method. In qualitative research, the Grounded theory method is a tool for building a conceptual model of manufacturing flexibility. The statistical sample of this section includes 20 experts familiar with the subject of manufacturing flexibility. The sampling method in the qualitative section is the Snowball Sampling method. The method of data collection in this part of the interview is semi-structured. The method of data analysis in the qualitative part is a three-step process of open, axial and selective coding. The results of this section show the model of manufacturing flexibility paradigm. The data collection tool in the quantitative part is a researcher-made questionnaire based on sub-categories and concepts obtained from the qualitative stage. The method of data analysis in this section is confirmatory factor analysis and structural equation modeling. The statistical sample in this section is 201 managers of food industry companies in East Azerbaijan province. The results show that environmental dynamics, increasing competitiveness and access to new markets are among the reasons for the need for manufacturing flexibility, in which automation and timely production are considered as industry strategies to achieve manufacturing flexibility; These factors have a direct effect on increasing organizational performance and customer satisfaction as a consequence of flexibility. The results also show that intervenors such as managerial factors, financial capability, etc. can influence strategies.

Aggregate production planning is a multi-objective problem which is influenced by managerial preferences which is rarely considered with these preferences in many researches. In this paper, a multi-product multi-objective aggregate-production-planning model has been proposed and implemented in an industrial ball-valves manufacturing company. In the first phase, preferences of various product groups have been determined via a multiple-attribute-decision-making method which is used as an input for the second phase. To do this, one of the outranking methods has been used because of the variety in the dimension and the nature of different attributes. In the second phase, a deterministic multi-objective mixed-integer mathematical model has been designed considering the needs of the company. This model not only concentrates on the benefits, but also considers the preferences of the products. The third objective function is decreasing work in process. To solve this model, ϵ-constraint method has been used leading to a set of Pareto-optimal solutions, enabling the decision-maker to choose the best solution by trading off between the three objective functions. So top managers are able to decide how to provide product preferences and how to decrease WIP products while the benefits remain reasonable. The results show that using the proposed approach in the case study has improved 35%, 28%, and 56% total benefit, total utility, and WIP products, respectively.

Given the increase of natural disasters, the community's need for health services has increased dramatically. Firstly, the condition of the injured people should be determined and then the treatment should be start, and in the event of increasing in the severity of the injured, these people should be transfer to the hospitals in the shortest possible time. On the other hand, another essential measure at the time of the accident is to send medicines and medical items at the appropriate time for treatment of injured. In this regard, we follow to design an emergency relief supply chain network including suppliers of medical items, treatment center, warehouses, and disaster points. Therefore, a location and inventory mathematical modeling is proposed to provide better services with the goal of minimizing the costs associated with locating and inventory of health systems. Then, to analyze the problem, we used the exact solution methods and the meta-heuristic method of genetic algorithm for 20 proposed problems. Results show that on a large scale, Genetic algorithm has a better performance to solve the problem of this research.

In the recent years, robots have been widely used in assembly systems as called robotic assembly lines where a set of tasks have to be assigned to stations and each station needs to select one of the different robots to process the assigned tasks. Our focus is on u-type layouts because they are widely employed in many industries due to their efficiency and flexibility . In these lines, a worker can be assigned to multiple stations located at entrance and exit sides. However, in many realistic situations, robots may be unavailable during the scheduling horizon for different reasons, such as breakdowns. This research deals with line balancing under uncertainty The Objective in this research is minimizing the cycle time for a given number of workstations and minimizing robot cost.This research deals with line balancing under uncertainty and presents one robust optimization model for balancing and sequencing of u-shaped robotic assembly line with considering set up times between task, failure robot times and preventive maintenance times for every robot. Since the NP-hard nature of the problem, multi-objective harmony search is developed to solve it. Numerical experiments also demonstrated that by increasing uncertainty level, the objective function values, cost and cycle times (minimum, maximum and average) increased. performance of the robust approach by the results, shows that in real conditions, considering the probability of event failure, values of cycle time and cost change significantly, which indicates the need to consider uncertainty, especially failure in robotic assembly lines.