摘要
物流监管企业承担供应链金融质押物配送职责,优化配送路径可以提高配送效率,节约配送成本,从而提高其盈利水平。以质押物配送路径总长度最小为优化目标,将其转换为经典TSP优化问题进行求解并建立数学模型。基于该数学模型,提出改进的遗传算法,针对遗传算法的选择、交叉和变异分别提出基于序的选择算子、基于最小代价树的交叉算子和基于随机点长度控制的变异算子。对比仿真实验表明,所改进的遗传算法比简单遗传算法收敛速度更快、全局寻优能力更好,是解决供应链金融质押物配送路径优化问题的有效方法。
Enterprises of logistics supervision undertake distribution functions of the pledge in supply chain fi-nance.The distribution route optimization can improve distribution efficiency and save the cost of distribution,so as to improve the profitability level of logistics enterprises.The distribution path length optimization of pledge in supply chain finance is converted to a classic Traveling Salesman Problem （TSP）.The mathematical model was established.An improved genetic algorithm was put forward based on the mathematical model.Then,sequence-based selection operator,minimum cost tree -based crossover operator and random length control -based mu-tation operator were proposed for the selection,crossover and mutation of the genetic algorithm,respectively. The simulation results between the improved genetic algorithm and the simple genetic algorithm show that the im-proved genetic algorithm has faster convergence,better global searching ability and it is an effective method to solve the pledge distribution path optimization problem in supply chain finance.
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2015年第4期949-955,共7页
Journal of Railway Science and Engineering
基金
湖南省教育科学研究资助项目(13C197)
关键词
遗传算法
改进
质押物
配送路径
优化
genetic algorithm
improvement
pledge
distribution path
optimization
