摘要
带集货和送货的多站点VRP问题作为VRP问题的一个分支,有着重大的研究价值.本文采用量子遗传算法求解MDVRPPD问题,并提出一种新的旋转门策略使得量子遗传算法的进化速度大大加快.实验证明,本文提出的改进算法和优化策略对比过去使用的启发式求解以及传统的量子遗传算法有较大优势,在时间控制上以及最优解的求解上都取得了满意的效果.
Multi-site VRP problem with collection and delivery as a branch of the VRP problem, has its significant research value. This paper uses quantum genetic algorithm for solving MDVRPPD problem,and proposes a new revolving-door policy which makes quantum genetic algorithm evolve faster. Experiments have shown that proposed improvements in algorithms and optimization strategy contrasting the past using quantum genetic algorithm of heuristic as well as traditional algorithms has a comparatively large advantage,and has achieved satisfactory results on optimal solutions to solve at the time control.
出处
《南京师大学报(自然科学版)》
CAS
CSCD
北大核心
2014年第1期99-103,共5页
Journal of Nanjing Normal University(Natural Science Edition)
关键词
量子遗传算法
多站点
车辆路径问题
物流配送
quantum genetic algorithm
multi-site
vehicle routing problem
logistics