A Fuzzy Multi-objective Programming for Optimization of Reverse Logistics for Solid Waste through Genetic Algorithms

Reverse Logistics for Solid Waste is an important problem concerning about economic and environment. This paper aims at determine the optimal locations and numbers of treatment facilities and transfer stations for municipal solid wastes. The proposed method is the combination of a fuzzy multi-objective programming and a genetic algorithm. The original fuzzy multiple objectives are appropriately converted to a single unified "min- max" goal, which makes it easy to design a genetic algorithm for the problem solving. So, a reverse logistics network for municipal solid waste is constructed. Finally, a case study of China proves the availability of our approach.