To solve the shortcomings of low convergence speed and poor local search ability when traditional genetic algorithm solves the vehicle routing problem with capacity constraints,an improved strategy for traditional genetic algorithm was proposed.The heuristic crossover operator based on the greedy strategy was used to enhance the ability of the algorithm to approach the optimal solution.In the mutation operation,the nearest neighbor search operator was introduced to narrow the range of gene mutation,and the single-point local insertion operator was used to improve the local optimization ability of the algorithm.A selection strategy combining elite selection and roulette method was adopted to maintain the diversity of the population and strengthen the global search ability of the algorithm.Example calculation test shows that compared with the traditional genetic algorithm,the average deviation of the solution is reduced by 70.25％,and the solution time is reduced by 87.41％.Compared with the ALNS and AGGWOA algorithms,it has higher solution quality and better stability.
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