A Solution for the Full-Load Collection Vehicle Routing Problem With Multiple Trips and Demands: An Application in Beijing

Abstract

Municipal solid waste (MSW) collection has become a major challenge for clean city management and social sustainable development in developing economies. A new variant of the collection vehicle routing problem (CVRP) is addressed with the characteristics of full loads and multiple trips of the collection vehicles, and multiple demands of the garbage facilities, which is called the collection vehicle routing problem of the garbage facilities (CVRPGF) in this study. Dummy customers are introduced to equivalently transform the CVRPGF problem to the vehicle routing problem with simultaneous pickup-delivery and time windows (VRPSPDTW). A parallel simulated annealing algorithm (Par-SAA) is developed to solve the VRPSPDTW problem. When applied to an international benchmark dataset, the computational results prove the superiority of the proposed algorithm, in which the number of collection vehicles (NV) in four instances is reduced by one. Finally, when the model and algorithm are applied to a real CVRPGF problem in the Xuanwu District of Beijing, the NV needed is reduced by 30%, and the total travel time is decreased by 12%. Thus, the effectiveness of the Par-SAA is demonstrated, and the proposed solution has practical value in China.

Keywords

• Municipal solid waste collection
• vehicle routing
• full load
• multiple trips
• multiple demands
• dummy customer