Variable Reduction Strategy Integrated Variable Neighborhood Search and NSGA-II Hybrid Algorithm for Emergency Material Scheduling

Developing a reasonable and efficient emergency material scheduling plan is of great significance to decreasing casualties property losses. Real-world (EMS) problems are typically large-scale possess complex constraints. An evolutionary algorithm (EA) one the effective methods for solving EMS problems. However, existing EAs still face challenges when dealing with or equality To handle above challenges, we apply idea variable reduction strategy (VRS) an problem, which can accelerate optimization process used obtain better solutions by simplifying corresponding Firstly, define allocation route model, neighborhood search NSGA-II hybrid (VNS-NSGAII) designed solve model. Secondly, utilize VRS simplify proposed model enable lower dimension fewer Furthermore, integrate VNS-NSGAII reduced prove effectiveness on VNS-NSAGII, construct two test cases, where case based multi-depot vehicle routing problem other combined initial 5·12 Wenchuan earthquake support situation. Experimental results show that improve performance standard VNS-NSGAII, enabling efficiency higher-quality solution.