期刊文献+

改进蚁群算法在应急VRP问题中的应用研究 被引量:3

Application of an Improved ACO in Emergency Logistics VRP
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摘要 提出一种改进的蚁群算法优化应急物流配送车辆路径问题算法,设计了应急物流配送车辆路径问题的数学模型,并利用计算机进行了仿真实验.实验结果表明,方法能有效解决应急物流配送车辆路径问题,具有一定的理论价值和实际意义. An improved ant colony algorithm in emergency logistics vehicle routing problem was, proposed. Math model of emergency logistics vehicle routing problem was constructed. The experimental results show that the ant colony algorithm possesses better optimization quantity and effect than the traditional ant colony algorithm. The algorithm possesses theory value and practical meaning.
出处 《数学的实践与认识》 CSCD 北大核心 2012年第9期91-95,共5页 Mathematics in Practice and Theory
基金 中央高校基本科研业务费专项基金(2Y20120210 20110104)
关键词 应急物流 蚁群算法 车辆路径问题 路径优化 emergency logistics ant colony algorithm vehicle routing problem routing optimization
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参考文献5

  • 1Wei Y, Arun K. Ant colony optimization for disaster relief operations[J]. Transportation Researeh part E: Logistics and Transportation Review, 2007, 43(6): 660-672.
  • 2Linet O. Emergeney logistics planning in natural disasters[J]. Annals of Operational' Researeh, 2004, 129(2): 217-245.
  • 3Dorigo M. Ant colony system: A cooperative learning approach to the traveling salesman problem[J]. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 53-66.
  • 4Sylvie Le H~garat-Mascle, Abdelaziz Kallel, Xavier Descombes. Ant Colony Optimization for Im- age Regularization Based on a Nonstationary Markov Modeling [J]. IEEE Transaction on Image Processing, 2007, 16(3): 865-878.
  • 5Girma S. Tewolde, Weihua Sheng. Robot Path Integration in Manufacturing Processes:Genetic Al- gorithm Versus Ant Colony Optimization[J]. IEEE Transactions on systems, man, and cybernetics-- Part A: systems and humans, 2008, 38(2): 278-287.

同被引文献26

  • 1张瑞锋,汪同三.新型遗传算法求解车辆路径问题研究[J].湖北大学学报(自然科学版),2012,34(2):239-242. 被引量:13
  • 2马良,朱刚,宁爱兵.蚁群优化算法[M].北京:科学出版社,2007:12-13,26-27.
  • 3王超学.遗传算法和蚁群算法及其在TSP问题和配电网重构问题中的应用研究[D].西安:西安理工大学,2004.
  • 4COLORNI A, DORIGO M, MANIEZZO V. Distributed optimization by ant colonies [ C ]. Proceedings of the 1 st European Conference on Artificial Life, Cambridge: The MIT Press, 1991, 142: 134-142.
  • 5STUTZLE T, HOOS H. MAX-MIN ant system and local search for the traveling salesman problem[ C]. Proceedings of 1997 IEEE International Conference on Evolutionary Computation, Indianapolis: IEEE, 1997 : 309 - 314.
  • 6Bullnheimer B, Hartl R F, Strauss C. An improved ant system algorithm for the vehicle routing problem[J]. Annals of Operations Research, 1999, 89 : 319-328.
  • 7Dofigo M, Stutzle T.蚁群优化[M].张军,胡晓敏,罗旭耀,等,译.北京:清华大学出版社,2007.
  • 8Solomon M M. Algorithms for vehicle routing and scheduling problem with time window constrains[J]. Operations Research, 1987,35 (2) : 254-266.
  • 9杨中秋,张延华.改进蚁群算法在交通系统最短路径问题的研究[J].现代电子技术,2009,32(8):76-78. 被引量:12
  • 10张锦,李伟,费腾.交叉变异蚁群算法在VRP问题中的应用研究[J].计算机工程与应用,2009,45(34):201-203. 被引量:8

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