Designing a sustainable fish closed-loop supply chain network under uncertainty

Fasihi, Maedeh; Tavakkoli–Moghaddam, Reza; Hajiaghaei–Keshteli, Mostafa; Najafi, Seyyed Esmaeil

doi:10.1007/s11356-023-25877-x

Cited by 6 publications

(2 citation statements)

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“…Perishable product supply chains gain increasing interest because the sustainable development concept is gradually being supported by society [15,39,40]. Liu, Zhu, Xu, Lu, and Fan [16] explored SPPSCN problems in emerging markets.…”

Section: Sustainable Perishable Products' Supply Chain Designmentioning

confidence: 99%

Optimization of Sustainable Supply Chain Network for Perishable Products

Pan,

Shan

2024

Sustainability

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In today’s perishable products industry, the importance of sustainability as a critical consideration has significantly increased. This study focuses on the design of a sustainable perishable product supply chain network (SPPSCN), considering the factors of economics cost, environmental impacts, and social responsibility. The proposed model is a comprehensive production–location–inventory problem optimization framework that addresses multiple objectives, echelons, products, and periods. To solve this complex problem, we introduce three hybrid metaheuristic algorithms: bat algorithm (BA), shuffled frog leaping algorithm (SFLA), and cuckoo search (CS) algorithm, all hybrid with variable neighbourhood search (VNS). Sensitivity to input parameters is accounted for using the Taguchi method to tune these parameters. Additionally, we evaluate and compare these approaches among themselves and benchmark their results against a reference method, a hybrid genetic algorithm (GA) with VNS. The quality of the Pareto frontier is evaluated by six metrics for test problems. The results highlight the superior performance of the bat algorithm with variable neighbourhood search. Furthermore, a sensitivity analysis is conducted to evaluate the impact of key model parameters on the optimal objectives. It is observed that an increase in demand has a nearly linear effect on the corresponding objectives. Moreover, the impact of extending raw material shelf life and product shelf life on these objectives is limited to a certain range. Beyond a certain threshold, the influence becomes insignificant.

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Section: Sustainable Perishable Products' Supply Chain Designmentioning

confidence: 99%

Optimization of Sustainable Supply Chain Network for Perishable Products

Pan,

Shan

2024

Sustainability

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“…An SSP approach via the epsilon-constraint was implemented to solved the model. Fasihi et al (2021), proposed a twoobjective mathematical model to design the fish closed-loop supply chain . A novel mathematical model has been presented to maximize customer demand responsiveness and minimize the network costs.…”

Section: Literature Reviewmentioning

confidence: 99%

A circular closed-loop supply chain network with an epsilon-constraint and NSGA-II approach

Jaferi

Shahin

Vasili

et al. 2023

Preprint

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Due to the lack of efficient waste management growing environmental pollutions leads to threatens the live of mankind and our planet. Good waste management need appropriate planning and monitoring at all different levels including designing, manufacturing, distribution, collection, recycling and disposal that require a circular approach. Circular supply chain, offers a new and compelling perspective to the supply chain sustainability domain. Therefor having proper solution approach for circular supply chains is of great value. To this end, in this paper suitable solution approaches has been presented for a multi-echelon, multi-product, multi-period and multi-objective mixed integer linear programing. This model is designed for a circular closed-loop supply chain that considered digital devices. The conflicting objectives of the model are to minimize total costs on the entire chain and environmental pollution and to maximize total rate of unemployment reduction. The Epsilon-constraint method is proposed to solve small size of the problem. A Pareto set of optimal solutions helped to assess the trade-offs involving the three objective. Because this problem is of NP-hard category, the non-dominated sorting genetic algorithm (NSGA-II) is used to find near optimal Pareto front for large size of the problem. To demonstrate the efficiency of the metaheuristic algorithm the answers obtained in small dimensions are compared with the answers obtained from the Epsilon-constraint method. The results show that the error percentage of the objective function compared to the epsilon method in all solved problems is less than 1%, which shows the effectiveness of the proposed algorithm. Reducing the solving time especially in the large dimensions of the problem is one of the advantages of this solution method. Using these methods allows decision makers to provide a set of efficient optimal solutions so that they can select the best point, according to the available budget and their organization policies.

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