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基于Greedy方法的动态配流模型与近似算法

郭瑞 郭进 苏跃斌 马亮

西南交通大学学报Issue(4):712-719,8.
西南交通大学学报Issue(4):712-719,8.DOI:10.3969/j.issn.0258-2724.2014.04.024

基于Greedy方法的动态配流模型与近似算法

Model and Approximation Algorithm for Dynamic Wagon-Flow Allocation Based on Greedy Strategy

郭瑞 1郭进 2苏跃斌 1马亮1

作者信息

  • 1. 西南交通大学信息科学与技术学院,四川成都610031
  • 2. 郑州轻工业学院计算机与通信工程学院,河南郑州450002
  • 折叠

摘要

Abstract

To develop a method for the intelligent generation of dynamic wagon-flow allocation,which can search and solve efficiently and timely perform adjustment,the multi-stage decision model was built based on greedy algorithm. By dividing the decision process into several stages of the marshaling sequence,a division method was proposed for dynamically sorting intervals in each stage according toΔti ,which is the value of the difference between the final formation time and the earliest sorting time mod standard break-up operation time. For each sorting interval,with train demand used as matching targets,five optimal selection algorithms of sorting trains were designed on the basis of different rules and strategies. The decision variables in each stage were queued to form the final sequence of sorting trains. Comparison tests of 8 groups show that simple rules and strategies can not guarantee a desirable solution,and whether a selection algorithm of matching targets is suitable depends on the number of sorting intervals and the selection strategy of sorting trains. Using the R_PPCD2-based algorithm (R_PPCD2 is a strategy which selects the sorting train by the matching degree of wagon-flow's orientation between the current stage and other remaining stages),a high-quality approximate solution for this type of NP-hard problem can be found in 2 s by proper adjustment of parameters such as break-up operation time,marshalling operation time,departure operation time.

关键词

编组站/动态配流/解体区间/启发式算法

Key words

marshalling stations/dynamic wagon-flow allocation/sorting interval/heuristic algorithms

分类

交通工程

引用本文复制引用

郭瑞,郭进,苏跃斌,马亮..基于Greedy方法的动态配流模型与近似算法[J].西南交通大学学报,2014,(4):712-719,8.

基金项目

国家自然科学基金资助项目(61203175);铁道部科技研究开发计划重点课题 ()

西南交通大学学报

OA北大核心CSCDCSTPCD

0258-2724

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