The vehicle routing programming of municipal solid waste collection under cognitive uncertainty

Abstract

The rapid development of online shopping has led to an increase in express parcels, thus the proliferation of solid waste from parcel packaging. There are many other phenomena that have arisen with rapid economic development that also led to the surge in municipal solid waste. It is urgent to pay attention to municipal solid waste collection. Unexpected disruptive events lead to cognitive uncertainty and cause municipal waste collection to fail to function properly. This article studies how to properly carry out vehicle planning to achieve the shortest driving distance under cognitive uncertainty. The community's time window and the amount of garbage in each community are taken as uncertain variables. Based on the uncertainty theory, an uncertain vehicle routing problem (VRP) model and an uncertain VRP with the loading constraint model are constructed, and the solution algorithms of these two models are given. Several applications are carried out to evaluate the effectiveness of the proposed models and algorithms. This article proposes for the first time the models and algorithms to study the VRP under cognitive uncertainty. The findings draw important practical implications for adjusting municipal solid waste collection planning and logistics during disruptive events.