计算机集成制造系统 ›› 2015, Vol. 21 ›› Issue (第6期): 1626-1636.DOI: 10.13196/j.cims.2015.06.027

• 产品创新开发技术 • 上一篇    下一篇

基于并行模拟退火算法求解时间依赖型车辆路径问题

穆东1,王超2+,王胜春3,周圣川4   

  1. 1.北京交通大学经济管理学院
    2.北京工业大学经济与管理学院
    3.北京交通大学计算机与信息技术学院
    4.青岛市勘察测绘研究院
  • 出版日期:2015-06-30 发布日期:2015-06-30
  • 基金资助:
    国家自然科学基金重点资助项目(71132008);国家自然科学基金面上资助项目(71473013);国家留学基金委公派访学资助项目(201207090034)。

Solving TDVRP based on parallel-simulated annealing algorithm

  • Online:2015-06-30 Published:2015-06-30
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71132008,71473013),and the China Scholarship Council,China(No.201207090034).

摘要: 为提高传统串行模拟退火算法求解时间依赖型车辆路径问题的效率,提出一种并行模拟退火算法。该算法首先使用前向插入启发式算法生成初始解,在主从式并行模拟退火算法框架下使用4种邻域搜索法对初始解进行优化。采用Figliozzi测试数据库(包含56个测试问题,顾客数均设定为100)对算法性能进行测试,结果表明在不同时间依赖型行驶函数情形下,当使用6个线程时,并行模拟退火算法相对于传统串行模拟退火算法可以得到近似于5倍的加速比,且均能在较快时间内得到比Figliozzi算法更优的解。因此,并行模拟退火算法能有效地求解时间依赖型车辆路径问题,并且可以灵活地扩展解决其他车辆路径问题和组合优化问题。

关键词: 车辆路径, 时间依赖型, 并行算法, 模拟退火

Abstract: To improve the efficiency of sequential Simulated Annealing(SA)for solving Time Dependent Vehicle Routing Problem(TDVRP),a parallel-Simulated Annealing(p-SA)algorithm was proposed.Push Forward Insertion Heuristic(PFIH)was implemented to generate an initial solution,and four kinds of local search moves within the structure of master-slave p-SA were developed to optimize the initial solution.Computational results were reported for 56 test problems with 100 customers from Figliozzi's benchmark,and the results showed that p-SA could get 5 times speedup when 6 threads was used by comparing with traditional sequential SA,and could get better solutions than Figliozzi's algorithm within an accepted computational time.Therefore,p-SA could solve TDVRP effectively and could be extended to handle other variants of vehicle routing problems and other combinatorial optimization problems.

Key words: vehicle routing, time dependent speeds, parallel algorithm, simulated annealing

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