计算机应用 ›› 2011, Vol. 31 ›› Issue (08): 2275-2278.DOI: 10.3724/SP.J.1087.2011.02275

• 典型应用 • 上一篇    下一篇

蚁群算法求解复杂集装箱装载问题

杜立宁1,张德珍2,陈世峰1   

  1. 1. 大连大学 信息工程学院,辽宁 大连116622
    2. 大连海事大学 信息科学技术学院,辽宁 大连116026
  • 收稿日期:2011-02-28 修回日期:2011-04-22 发布日期:2011-08-01 出版日期:2011-08-01
  • 通讯作者: 杜立宁
  • 作者简介:杜立宁(1986-),女,山东德州人,硕士研究生,主要研究方向:虚拟现实;张德珍(1973-),男,辽宁大连人,副教授,博士,主要研究方向:虚拟现实、智能信息、布局优化算法;陈世峰(1986-),男,湖南邵阳人,硕士研究生,主要研究方向:企业信息化。
  • 基金资助:

    中国博士后科学基金资助项目(20080441107);大连市青年基金资助项目(2008J23JH028)

Solution to complex container loading problem based on ant colony algorithm

Li-ning DU1,De-zhen ZHANG2,Shi-feng CHEN1   

  1. 1. School of Information Engineering, Dalian University, Dalian Liaoning 116622, China
    2. College of Information Science and Technology, Dalian Maritime University, Dalian Liaoning 116026, China
  • Received:2011-02-28 Revised:2011-04-22 Online:2011-08-01 Published:2011-08-01
  • Contact: Li-ning DU

摘要: 针对复杂集装箱装载问题(CLP),应用启发式信息与蚁群算法求解了最优装载方案。首先,建立了复杂集装箱装载问题的数学模型,利用蚁群算法对解空间的强搜索能力、潜在并行性及可扩充性,结合三空间分解策略将布局空间依次分割;然后,装入满足约束条件的最优货物块,完成不同大小三维矩形货物的装载布局。在此基础上,设计了基于空间划分策略的蚁群算法。最后以700件货物装入40尺(12.025m)高柜箱进行计算,结果表明该方法能提高集装箱的空间利用率,同时兼顾了多个装载约束条件,可应用性好。

关键词: 蚁群算法, 集装箱装载问题, 启发式信息, 一次性装载

Abstract: In view of the complex Container Loading Problem (CLP), the optimal loading plan with heuristic information and the ant colony algorithm was proposed. Firstly, a mathematical model was generated. Considering the strong search ability, potential parallelism and scalability of ant colony algorithm, the proposed algorithm was combined with the triple-tree structure to split the layout of space in turn. Then, the three-dimensional rectangular objects of different sizes were placed to the layout space under the constraints. An ant colony algorithm based on spatial partition was designed to solve the optimal procedure. Finally, a design example that 700 pieces of goods were loaded into a 40-foot (12.025m) high cubic was calculated. The experimental results show that the proposed method can enhance the utilization of the container and it has a strong practicality.

Key words: ant colony algorithm, Container Loading Problem (CLP), heuristic information, one-time loading

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