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.