计算机与现代化 ›› 2011, Vol. 1 ›› Issue (11): 3-4.doi: 10.3969/j.issn.1006-2475.2011.11.002

• 算法分析与设计 • 上一篇    下一篇

物流运输网络优化研究

江卫星   

  1. 镇江高等专科学校,江苏镇江212003
  • 收稿日期:2011-08-11 修回日期:1900-01-01 出版日期:2011-11-28 发布日期:2011-11-28

Research on Optimization Logistics Transportation Network

JIANG Wei-xing   

  1. Zhenjiang College, Zhenjiang 212003, China
  • Received:2011-08-11 Revised:1900-01-01 Online:2011-11-28 Published:2011-11-28

摘要: 物流运输网络中的固定费用运输问题( fcTP)是物流运输中的高级问题,较难得到最优解。本文提出一种基于免疫克隆遗传算法来解决多目标固定费用运输问题。该算法将运输问题的目标函数和约束条件作为抗原,将问题的可行解作为抗体,而抗体与抗原之间的亲和度就用可行解的目标函数值来表示,通过判断抗体与抗原的亲和度和抗体的浓度来克隆选择个体进入下一代。仿真结果表明,免疫克隆遗传算法在固定费用运输问题应用中得到较好的Pareto最优集和Pareto边界。

关键词: 免疫, 克隆, 遗传算法, 固定费用运输问题

Abstract: Fixedcharged Transport Problem (fcTP) in the logistics transport networks is an advanced problem, and it is difficult to obtain optimal solution. This paper puts forward a Genetic Algorithm based on immune clone algorithm to solve multiobjective fixed charge transportation problem. In the algorithm, the transportation problem target function and constraints are regarded as antigens, problem feasible solution as antibodies, compatibility degree between antigen and antibody are represented by the feasible solution to the objective function, through the judgment of compatibility degree between antibody and antigen and of antibody concentration to select individuals to clone the next generation. Simulation results show that the immune cloning genetic algorithms in the application of the fixed charge transportation problem gets better Pareto optimality sets and Pareto boundary.

Key words: immunity, cloning, genetic algorithm, fixedcharged transportation problem