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Abstract
A waste collection problem is one of the most important problems in reverse logistics. This paper presents a mathematical model for waste collection problem and considers waste collection from customers’ location and waste disposal in compatible disposal facilities. The fleet of vehicles is heterogeneous and vehicles have multi-separated compartments. Vehicles have different capacity, different travel time and distance limitations, and different variable and fixed costs. Vehicles start their route from depots, collect wastes from customers’ location, and move to disposal centers to unload waste in the related disposal facility, and then return to depots. We should choose appropriate location for depots and disposal facilities from potential locations with respect to economic and social objectives. To solve the model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) are proposed. Finally, the computational results are compared and analyzed.