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文章基本信息

  • 标题:Vehicle Scheduling Optimization Based on Chaos Ant Colony Algorithm in Emergency Rescue
  • 本地全文:下载
  • 作者:Lingxia Liu ; Xuexia Gao ; Qiang Song
  • 期刊名称:International Journal of Security and Its Applications
  • 印刷版ISSN:1738-9976
  • 出版年度:2016
  • 卷号:10
  • 期号:2
  • 页码:63-74
  • DOI:10.14257/ijsia.2016.10.2.06
  • 出版社:SERSC
  • 摘要:Aiming to the demand and characteristics of vehicle scheduling optimization problem in emergency rescue, this paper establishes a multi-objective optimization model, which takes minimizing variable bidirectional distance, path risk and cost as the optimization target. To avoid the prematurely falling into local optimization of ant colony system(ACS)algorithm, and to improve the algorithm adaptability, computational efficiency and the quality of optimal solution, this paper proposed and realized a chaos-based improved ant colony system algorithm, which can overall updates the chaos disturbance to pheromone. Simulation results show that the algorithm is feasible, which can well meet the demand of vehicle scheduling optimization in emergency rescue.
  • 关键词:Emergency; vehicle scheduling; chaos; ant colony system
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