Sustainable Closed-Loop Supply Chain: A Case Study Of Dairy Industry

Abstract

Recent advancements and innovations in the food and beverage industry have raised concerns about the environmental impact of food and beverage waste and the safety of agricultural products. Recently, reverse logistics has been implemented to resolve these problems. It is also possible to reduce the environmental impact of these byproducts and return them to the network through the establishment of composting facilities and the design of an optimal supply chain distribution network. In this article, a mixed-integer linear programming mathematical model for a dairy supply chain network is devised. The proposed model seeks to optimize total profit, environmental impacts of facility establishment, dairy processing, and transportation between each level, as well as social impacts such as employment opportunities. To address the proposed model, efficient and well-known historical stochastic agumented ε-constraint and genetic algorithm in metaheuristic are employed. In addition, algorithms are devised flexibly to facilitate intensification and diversification phases. The quality of these two algorithms is subsequently evaluated and contrasted