摘要
针对车辆在负载和空载状态下不同的成本核算模型,提出了两阶段算法求解最小配送成本:第一阶段用改进的扫描算法求得满足问题约束条件的若干组非同质化的初始解;第二阶段采用这些解作为多样化的初始种群,并用改进的单亲遗传算法进行全局、大范围搜索,最终求得满意解.实例计算表明,算法能在较短的时间内求得理想解,满足了物流配送企业深挖内部潜力、有效控制成本的现实需要.
Aiming at the different costing model for vehicle at load or no-load state, a two-stage algorithm for solving the minimum distribution costs was proposed. At the first stage, an enhanced sweeping algorithm was used to obtain various groups of non-homogeneity initial solution which met the constraints. At the sec- ond phase, these solutions were used as diverse initial population, an improved single parent genetic algo- rithm was used to perform overall and large range searching and finally the satisfactory result was obtained. Practical calculation shows that the algorithm can obtain a rnore satisfactory solution in a short period of time, which meets the actual needs for logistics companies to root out the internal potential to control the cost effectively.
出处
《成都大学学报（自然科学版）》
2012年第3期235-238,共4页
Journal of Chengdu University（Natural Science Edition）
