东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2008, Vol. 29 ›› Issue (5): 633-636.DOI: -

• 论著 • 上一篇    下一篇

钢铁企业产成品转库车辆路径问题优化

刘士新;董国栋;张涛;   

  1. 东北大学流程工业综合自动化教育部重点实验室;东北大学流程工业综合自动化教育部重点实验室;上海财经大学信息管理与工程学院 辽宁沈阳110004;辽宁沈阳110004;上海200433
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2008-05-15 发布日期:2013-06-22
  • 通讯作者: Liu, S.-X.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(70301007,70771020,70501018);;

Modelling and optimization algorithm for solving vehicle routing problems of finished product re-depositing in steel plants

Liu, Shi-Xin (1); Dong, Guo-Dong (1); Zhang, Tao (2)   

  1. (1) Key Laboratory of Integrated Automation of Process Industry, Northeastern University, Shenyang 110004, China; (2) School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2008-05-15 Published:2013-06-22
  • Contact: Liu, S.-X.
  • About author:-
  • Supported by:
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摘要： 分析了钢铁企业产成品转库问题的特点,通过将转库任务分解的方法将原问题转化为具有最迟访问时间约束和同时访问车辆数限制的车辆路径优化问题,建立了转换后问题的0-1规划数学模型,针对模型的特点设计了迭代局域搜索算法.算法初始解由贪婪算法生成,局域搜索过程采用4种常用局域搜索算子的混合,摄动过程采用变强度的2-opt*算子.该算法可以同时实现转库车辆指派和车辆路径优化.通过仿真生成的算例对模型和算法进行了验证.实验结果表明,该模型和算法是解决该类问题的有效方法.

关键词: 产成品转库, 车辆指派, 车辆路径问题, 迭代局部搜索, 摄动

Abstract: The characteristics of finished product re-depositing problems in steel plants are analyzed. After transportation tasks being decomposed, the original problems are transferred to vehicle routing problems with constraints of latest visiting time and of number of vehicles which are simultaneously visiting the same warehouse. Consequently, a 0-1 program model is presented, and an iterated local search (ILS) algorithm is designed to solve the problems. The initial solution is generated by a greedy heuristic approach. Local search procedure is designed by combining four well-known local search operators. Perturbation operator adopts variable intension 2-opt* operator. The vehicle dispatching and vehicle route optimizing can simultaneously be done with the algorithm. The model and algorithm are tested by citing randomly generated problem instances. Computational results show that the model and algorithm are effective for solving this kind of problems.

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