摘要
研究了多车场多配送中心车辆的路径问题,以提高物流配送效率.在分析了问题有效解的基础上,制定了相应的染色体分段编码,给出了合适的适应值函数,使杂交变异得到的新基因具有更好的健壮性.为了克服传统遗传算法早熟的缺点,作者结合模拟退火算法和小生境遗传算法,以无序的方式进行杂交和随机点的基因变异,保证了进化后的种群多样性,并且杂交选择方式使得算法收敛性较佳.通过实例检验,在可行解的集合内该方法收敛于近似最优解.
Studying VRP of multi-depots and multi-distribution centers can improve efficiency of logistics and distribution.Corresponding code of chromosome segment is set in the analysis of effective solutions for the problem.The appropriate fitness function ensures that the hybrid gene mutation has better robustness.Combined with simulated annealing algorithm and niche genetic algorithm disorderly hybrid approach and mutations of random point are used overcoming the premature shortcoming of the traditional genetic algorithm.Population diversity reserves as to this evolution and the method of hybrid determines the convergence of the algorithm.The instance shows that this algorithm could find approximate optimal solution efficiently.
出处
《陕西科技大学学报（自然科学版）》
2011年第2期69-74,共6页
Journal of Shaanxi University of Science & Technology
关键词
物流
遗传算法
满载运输
车辆路径问题
优化
logistics
genetic algorithm
full loaded transportation
vehicle routing problem
optimize
