Evolutionary Large‐Scale Multi‐Objective Optimization in Logistics Scheduling

Evolutionary algorithms (EAs) are a type of popular metaheuristic algorithms and have exhibited good performance in addressing multi‐objective logistics scheduling problems. This chapter presents two state‐of‐the‐art EAs for two typical large‐scale multi‐objective logistics scheduling problems: an evolutionary multi‐objective route grouping‐basedheuristic algorithm (EMRG‐HA) for the vehicle routing problem (VRP) and a clustering‐based surrogate‐assisted multi‐objective EA with reference point adaptation (AR‐MOEA+SA) for the facility location problem (FLP). The VRP presented in this chapter is the classic and basic capacitated vehicle routing problem, which serves as a reliable test bed for many VRP optimization algorithms. The FLP presented in this chapter is a real‐world application in emergency management: the uncertain shelter location problem.