Multi-Objective Optimization of Municipal Solid Waste Collection Based on Adaptive Large Neighborhood Search

Abstract

To address the dual challenges of reducing carbon emissions and operating costs in municipal solid waste collection, this paper investigates the vehicle routing problem (VRP) for municipal solid waste collection and transportation, which significantly affects the transportation costs and efficiency. An analysis has shown substantial disparities in workload distribution across different routes, highlighting the need to consider both the workload balance and cost efficiency. Therefore, considering the factors of workload disparities and costs, a multi-objective VRP model is formulated, and a multi-objective adaptive large neighborhood search (MOALNS) algorithm based on balance remove and balance insert heuristics is proposed to solve the above problem. The proposed algorithm is compared with two classical multi-objective algorithms, and the results show its competitiveness. The designed model can effectively reflect the conflict between minimizing costs and balancing disparities in employee workloads.