Cold-water farmed fish chain supply chain network design considering uncertainty conditions: A case study of trout supply chain network in Mazandaran

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.