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  • 标题:Ant Colony Optimization for Capacity Problems
  • 本地全文:下载
  • 作者:Tad Gonsalves ; TakafumiShiozaki
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2015
  • 卷号:5
  • 期号:1
  • 页码:157-164
  • DOI:10.5121/csit.2015.50116
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:This paper deals with the optimization of the capacity of a terminal railway station using theAnt Colony Optimization algorithm. The capacity of the terminal station is defined as thenumber of trains that depart from the station in unit interval of time. The railway capacityoptimization problem is framed as a typical symmetrical Travelling Salesman Problem (TSP),with the TSP nodes representing the train arrival /departure events and the TSP total costrepresenting the total time-interval of the schedule. The application problem is then optimizedusing the ACO algorithm. The simulation experiments validate the formulation of the railwaycapacity problem as a TSP and the ACO algorithm produces optimal solutions superior to thoseproduced by the domain experts.
  • 关键词:Travelling Salesman Problem; Ant Colony Optimization; Capacity Problems; Meta-heuristic;Optimization; Soft Computing.
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