Designing a new multi-echelon multi-period closed-loop supply chain network by forecasting demand using time series model: a genetic algorithm

Safaei, Shahab; Ghasemi, Peiman; Goodarzian, Fariba; Momenitabar, Mohsen

doi:10.1007/s11356-022-19341-5

Cited by 37 publications

(14 citation statements)

References 35 publications

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“…The third thing is the capacities changes in various centers in the designed CLBSCN (Safaei et al, 2022 ). The result of capacity variation in different centers like BFC, NBB, Hospitals, and BDC are shown in Fig.…”

Section: Implementation and Resultsmentioning

confidence: 99%

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Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

et al. 2022

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Reconfiguring the structure of the supply chain network is one of the most strategic and vital decisions in designing a supply chain network. In this study, a Closed-Loop Blood Supply Chain Network (CLBSCN) considering blood group compatibility, ABO-Rh(D), and blood product shelf life has been studied to determine the best strategic and tactical decisions simultaneously considering lateral resupply/transshipment and service-level maximization. Several vital parameters, including supply and demand, are considered fuzzy numbers to approximate reality due to the nature of the world. Furthermore, two crucial factors include ABO-Rh(D) and blood product shelf life considered, while the concept of lateral resupply governs the interconnections of hospitals’ excess blood units. We propose a fuzzy multi-objective Mixed-Integer Non-Linear Programming (MINLP) model to consider two critical objective functions: minimizing the total costs of the network and maximizing the minimum service level to the patients at each Hospital. The fuzzy multi-objective MINLP model is converted to a deterministic multi-objective model using the equivalent auxiliary crisp model to deal with uncertainty. Then, by utilizing two interactive fuzzy solution approaches, the results have been compared based on a real case study to suggest the best solution for the proposed model. Also, we conduct sensitivity analysis on essential parameters such as demand, supply, and capacity to understand how these parameter variations impact two proposed objective functions. Then, the proposed model is tested on a real case study for model validation. The results confirmed that considering the lateral resupply could significantly save the costs of the designed network by a total of $343,000. Interestingly, maximizing the minimum service level at hospitals increased the service level from 58% to 68%.

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Section: Implementation and Resultsmentioning

confidence: 99%

“…The proposed mathematical model in the previous section has non-linear equations that need to be converted to linear equations (Momenitabar et al, 2022 ; Safaei et al, 2022 ). First, the second objective function shown by Eq.…”

Section: Notations Of the Modelmentioning

confidence: 99%

Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

et al. 2022

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“…Moreover, a Nondominated Sorting Genetic Algorithm is developed for solving large-sized problems. Safaei et al [19] addressed a new multi-echelon multi-period closed-loop supply chain network to minimize the total costs of the network. The echelons include suppliers, manufacturers, distribution centers, customers, and recycling and recovery units of components in the proposed network.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In equations (19) to (23), we assumed that there is at least one facility of each type in every period.…”

Section: Picture Of Problem Statementmentioning

confidence: 99%

A Multiobjective Model for Optimizing Green Closed‐Loop Supply Chain Network under Uncertain Environment by NSGA‐II Metaheuristic Algorithm

Hassangaviar

Naderi

Etebari

et al. 2022

Discrete Dynamics in Nature and Society

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Nowadays, due to growing development and competitiveness in global markets of products, companies are forced to make significant efforts for supply procurement, production, and goods distribution in order to survive in the market and be able to respond to their customers’ needs as quickly and cost-efficiently as possible. In this regard, supply chain management is considered a crucial indicator. This study presents a multiobjective, multifacility, closed-loop supply chain under uncertain environments considering green supply chain aspects. The model is designed with multiple products, periods, plants, customer markets, collection centers, recycle centers, distribution centers, return facilities, product recovery facilities, and suppliers. After modeling the study, the model is solved by the Nondominated Sorting Genetic Algorithms (NSGA-II) in order to rank the optimum solutions. The efficiency of the research model is indicated by the results and depicted graphs in the present study. Results show that the exact value of the triple objective functions is calculated. Also, the problem is solved in small, medium, and large dimensions. Then, the accuracy of the proposed model compared to the metaheuristic method is shown. Finally, by performing sensitivity analysis, we showed that target functions are less sensitive to reducing the capacity of centers.

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“…Safaei et al [20] presented a new multi-period and multiechelon mathematical model for closed-loop supply chain. ey forecasted demand using time series model using autoregressive integrated moving average (ARIMA).…”

Section: Introductionmentioning

confidence: 99%

Presenting a Multi‐Echelon and Multi‐Product Model for Inventory Control considering Shortages Using a Heuristic Algorithm

Ara

Toofani

Kaveh

et al. 2022

Discrete Dynamics in Nature and Society

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In the present study, a mathematical model is provided for inventory management in a three-level supply chain including a supplier, a manufacturer, and a distributor, taking into account the potential for product deficiency. Significant parameters such as the optimal order size for raw materials, optimal production rate, optimal allowed deficiencies at each supply chain level, the of the vehicles and the number of times the products are delivered between the supply chain components have been provided aiming at minimizing inventory management costs in the supply chain. The problem was solved using a heuristic algorithm. The proposed model is implemented for 20 different numerical examples. According to the results, the difference between the solutions obtained from the algorithm and the solutions obtained from the optimal values with the real variables is an average of 1.52%.

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Designing a new multi-echelon multi-period closed-loop supply chain network by forecasting demand using time series model: a genetic algorithm

Cited by 37 publications

References 35 publications

Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

Robust possibilistic programming to design a closed-loop blood supply chain network considering service-level maximization and lateral resupply

A Multiobjective Model for Optimizing Green Closed‐Loop Supply Chain Network under Uncertain Environment by NSGA‐II Metaheuristic Algorithm

Presenting a Multi‐Echelon and Multi‐Product Model for Inventory Control considering Shortages Using a Heuristic Algorithm

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