Design of Forward/reverse Logistics with Environmental Consideration

An increase in environmental issues has encouraged the consideration of various factors that influence the environment. In this regard, the green supply chain has attracted the attention of researchers because of its considerable impacts on the environment. This study, therefore, was an attempt to design a forward/revers logistics network by putting emphasis on some environmental issues like the quantity of CO2 emission in its model. In this logistics network, three objective functions including minimizing the total cost and quantity of CO2 emission as well as maximizing the satisfaction of customers are considered simultaneously. This persuaded the researchers to adopt multi-objective optimization methods. Thus, Non-dominated sorting genetic algorithms (NSGA-ӀӀ) and Multi-objective particle swarm optimization (MOPSO) are proposed to cope with the problem. Finally, the results of the experiments on several test problems are verified by GAMS software. They confirm the superiority of NSGA-ӀӀ over MOPSO in terms of all comparison metrics.