计算机应用 ›› 2012, Vol. 32 ›› Issue (02): 440-443.DOI: 10.3724/SP.J.1087.2012.00440

• 人工智能 • 上一篇    下一篇

考虑区间约束的物流网络双层规划模型及算法

李利华1,2,符卓2,胡正东2,3   

  1. 1. 长沙理工大学 交通运输工程学院,长沙 410004
    2. 中南大学 交通运输工程学院,长沙 410075
    3. 南华大学 政治与公共管理学院,湖南 衡阳 421001
  • 收稿日期:2011-08-08 修回日期:2011-09-22 发布日期:2012-02-23 出版日期:2012-02-01
  • 通讯作者: 李利华
  • 作者简介:李利华(1979-),男,湖北红安人,讲师,博士研究生,主要研究方向:物流工程;
    符卓(1960-),男,海南琼海人,教授,博士生导师,主要研究方向:物流工程;
    胡正东(1975-),男,湖南衡阳人,副教授,博士研究生,主要研究方向:物流工程。
  • 基金资助:
    国家自然科学基金资助项目(70671108);湖南省科技计划项目(2010FJ6016)

Bilevel programming model and algorithm for logistics network with interval constraints

LI Li-hua1,2,FU Zhuo1,HU Zheng-dong1,3   

  1. 1. School of Traffic and Transportation Engineering, Central South University, Changsha Hunan 410075,China
    2. School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha Hunan 410004, China
    3. School of Political Science and Public Administration, University of South China, Hengyang Hunan 421001, China
  • Received:2011-08-08 Revised:2011-09-22 Online:2012-02-23 Published:2012-02-01
  • Contact: LI Li-hua

摘要: 考虑物流网络需求的不确定性,利用区间参数度量不确定性变量与参数,建立区间需求模式下的物流网络双层规划模型,设计了一种含区间参数与变量的递阶优化遗传算法,通过定义问题求解的风险系数与最大决策偏差,给出适合物流网络结构的区间运算准则,实现模型的确定性转化。以区间松弛变量与0-1决策变量定义初始种群,通过两阶遗传操作运算,求解不同情景下双层规划目标的区间最优解与节点决策方案。算例测试表明算法求解的可操作性更强,求解结果具有区间最优解与情景决策的优越性。

关键词: 物流网络设计, 不确定性, 区间参数, 双层规划模型, 遗传算法

Abstract: Considering the uncertainty of logistics demand network, the interval number was used to measure uncertain variables and parameters. The bilevel programming model of logistics network under interval demand mode was established and a hierarchical interval optimization genetic algorithm with interval variables and parameters was designed. The risk coefficient and the maximum decision-making deviation were defined to solve the problem, and the rules for logistics network structure were given to transform the model with certainty. The initial population was defined by interval slack variables and 0-1 decision variable, with two-stage genetic operation to solve interval optimal solution and node decision-making scheme of bilevel programming objects under different scenarios. The results of tested example show that the operability of the algorithm is much stronger and the solution result has superiority in interval optimal solution and scenario decision.

Key words: logistics network design, uncertainty, interval parameter, bilevel programming model, Genetic Algorithm (GA)

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