Elite Group-Guided Genetic Algorithm for Solving Vehicle Pouting Problem
In order to improve the defects of genetic algorithm when solving Vehicle Pouting Problem,such as easy to fall into local optimization and large amount of computation.The improved circle algorithm is used to optimize individuals,improve the quality of the population.The rapid evolution strategy is formed through the guidance of elite groups.The crossover,mutation and selection operations of traditional genetic algorithms are improved to generate more populations and enhance the efficiency of evolution.The feasibility and effectiveness of the proposed algorithm are verified on 8 TSPLIB benchmark problems.Experimental results show that the elite group-guided genetic algorithm can effectively avoid falling into the local optimal solution,improve the convergence rate of the population,and has advantages on accuracy rate and stability.
genetic algorithmcombinatorial optimizationvehicle pouting problem
万方数据
维普
