计算机科学 ›› 2018, Vol. 45 ›› Issue (8): 198-202.doi: 10.11896/j.issn.1002-137X.2018.08.035

• 人工智能 • 上一篇    下一篇

基于改进智能水滴算法的多目标供应链最优模型

方青1,2, 邵嫄2   

  1. 华中科技大学管理学院 武汉4300741
    武汉科技大学管理学院 武汉4300652
  • 收稿日期:2017-05-11 出版日期:2018-08-29 发布日期:2018-08-29
  • 作者简介:方 青(1974-),男,博士,讲师,主要研究方向为物流和供应链建模与优化决策、算法,E-mail:fangqing@wust.edu.cn; 邵 嫄(1984-),女,博士,讲师,主要研究方向为系统工程与优化决策、算法,E-mail:68228155@qq.com(通信作者)。
  • 基金资助:
    本文受国家自然科学基金青年资助项目(71501147),湖北省大学生创新创业训练计划项目(201510488028)资助。

Optimal Model of Multi-objective Supply Chain Based on Improved IWD Algorithm

FANG Qing1,2, SHAO Yuan2   

  1. School of Management,Huazhong University of Science and Technology,Wuhan 430074,China1
    School of Management,Wuhan University of Science and Technology,Wuhan 430065,China2
  • Received:2017-05-11 Online:2018-08-29 Published:2018-08-29

摘要: 为了最大限度地降低制造型供应链的销售成本并缩短供货时间,提出了一种基于改进智能水滴算法的多目标供应链优化模型。该模型通过在选项选择期间同时考虑成本和时间来提高供应链效率,并能够将制造型供应链中的销售成本和交货时间最小化。通过使用帕累托最优准则对传统的智能水滴算法进行修改,从而得到一个帕累托集,以实现两个目标的最小化。通过3个实例对所提算法进行了测试,并采用世代距离和超区域比指标将其与蚁群优化算法进行了比较。实验结果显示,所提方法的性能更优,生成的解集更接近真实帕累托集,能够覆盖更大的解区域面积,且计算效率较高。

关键词: 多目标供应链, 帕累托最优, 制造型供应链, 智能水滴算法

Abstract: In order to minimize the selling cost and delivery time of manufacturing supply chain,a multi-objective supply chain optimization model based on improved intelligent water drop algorithm was proposed.The model improves the efficiency of the supply chain by considering both cost and time during option selection,and minimizes the sales cost and leads time in the manufacturing supply chain simultaneously.By using the Pareto optimality criterion,the traditional intelligent water drop algorithm is modified to obtain a Pareto set to minimize the two objectives.The algorithm was tes-ted by three examples andcompared with the ant colony optimization algorithm using the generation distance and hypera-rea ratio index.The results show that the performance of the proposed method is more excellent and the generated set is closer to the real Pareto set to cover a larger area of solution region,with the calculation efficiency being high.

Key words: Intelligent water drop algorithm, Manufacturing supply chain, Multi-objective supply chain, Pareto optimality

中图分类号: 

  • TP183
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