| dc.description.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 | en_US |
