期刊文献+

旅行商问题优化解之间关系的分析 被引量:2

Relationship Analysis Between Optimal Solutions of TSPs
下载PDF
导出
摘要 旅行商问题是经典的组合优化NP难题之一,学术界一直致力于建立在合理的计算时间内精确或近似求解问题的算法.近似算法常求得的高质量近似优化解与全局最优解之间边交集不为空,建立了两者之间及与全局最优解之间的特定关系,通过数学分析建立量化关系模型,利用实验确立模型中相关参数的先验概率.据此建立的随机TSP裁减过程大幅度裁减问题的求解规模;在求解过程中亦能高概率确定属于全局最优解的边,以提高问题求解效率和质量. Traveling Salesman Problem is one of the typical NP-hard problems in the field of combinatorial optimization. Academe commits himself to finding new algorithms for solving exactly or approximately TSP in reasonable computing time for a long time. The fact,which the intersection between high-quality optimal solutions found by approximate algorithm and global optimal solutions ,establishes two kind of special relationships ,the one is between them, and the other one is among high-quality optimal solutions. The quantizing relationship model can be set up through mathematic analysis, and the prior probability of correlative parameters in the model is computed in virtue of experiment. By utilizing it, the stochastic TSP cutting procedure cuts sharply down problem solving scale. The edges can be identified in high probability whether or not they belong to the edge set of global optimal solutions so that the solving efficiency and quality is improved effectively.
出处 《小型微型计算机系统》 CSCD 北大核心 2008年第5期879-884,共6页 Journal of Chinese Computer Systems
基金 国家自然科学基金-广东中生代典型侵入岩隆升过程研究项目(40473029)资助
关键词 旅行商问题 全局最优解 局部最优解 裁减 求解质量 traveling salesman problem global optimal solution local optimal solution cutting solution quality
  • 相关文献

参考文献13

  • 1Carpaneto G,Toth P. Some new branching and bounding criteria for the asymmetric traveling salesman problem[J]. Management Science, 1980,26(7):736-743.
  • 2Dantzing G B. Solution of a large scale traveling salesman problem[J]. Operations Research, 1954,20:393-410.
  • 3Bellman R. Dynamic programming treatment of the traveling salesman problem[J]. Journal of the ACM, 1962,9 (1) : 61-63.
  • 4Gerfenstette J J, Gopal R, Rosmaita B,et al. Genetic algorithms for traveling salesman problem[C], Proceedings of an International Conference on Genetic Algorithms and Their Applications, 1985,160-168.
  • 5Tseng C C, Tsai C F,Tsai C W. A new hybrid heuristic approach for solving large traveling salesman problem[J]. Information Sciences, 2004,166 (1-4) : 67-81.
  • 6Gutin G, Yeo A. Polynomial approximation algorithms for the TSP and the QAP with a factorial domination number[J]. Discrete Applied Mathematics, 2002,119(1-2) :107-116.
  • 7Cochrane E M ,Beasley J E. The co-adaptive neural network approach to the euclidean traveling salesman problem[J]. Neural Networks, 2003, 16(10):1499-1525.
  • 8Boese K. Cost versus distance in the traveling salesman problem [R]. Technical Report, TR-950018, CS Department, UCLA, 1995.
  • 9David A, Robert B,Vasek C. Concorde network optimization package [CP/OL]. http://www. tsp. gatech. edu/concorde/downloads/codes/src/co031219.tgz. 1997-08-08/2006-11-07.
  • 10University of Heidelberg. Traveling salesman problems library [EB/OL]. http://www. iwr. uni-heidelherg. de/groups/comopt/software/TSPLIB95/. 1997-08-08/2006-11-07.

同被引文献20

  • 1DORIGO M, COLOMI A, MANIEZZO V. Distributed optimization by ant colonies [ C ]//Proc of the First European Conf of Artificial Life. Paris: Elsevier, 1991: 134-142.
  • 2DORIGO M, MAN1EZZO V, COLOM! A. The ant system: optimization by a colony of cooperating agents [ J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 1996( 1 ) : 29-41.
  • 3DORIGO M, GAMBARDELLA L M. Ant colony system: a cooperative learning [ J]. IEEE Transactions on Evolutionary Computation, 1997, 1 ( 1 ) : 53-66.
  • 4STUZLE T, HOOS H. MAX-MIN ant system and local search for the traveling salesman problem [ C ]//IEEE Intl Conf on Evolutionary Computation. Indianapolis: IEEE Press, 1997 : 309-314.
  • 5BLUM C, DORIGO M. The hyper-cube framework for ant colony optimization [ J ]. IEEE Trans Systems, Man, and Cybernetics, 2004, 34(2): 1161-1172.
  • 6REIMANN M. Guiding ACO by problem relaxtion: a case study on the symmetric TSP [ J ]. Lecture Notes in Computer Science, 2007, 4771:45-55.
  • 7JONES T, FORREST S. Fitness distance correlation as a measure of problem difficulty for genetic algorithm [ C ]//Proceeding of the 6th International Conference on Genetic Algorithm. San Mateo, CA: Morgan Kaufmann, 1995: 184-192.
  • 8RUSSELL R A. An effective heuristic for the m-tour traveling salesman problem with some side conditions[ J]. Operations Research, 1977,25(3) :517-524.
  • 9BEKTAS T. The multiple traveling salesman problem: an overview of formulations and solution procedures [ J ]. Omega, 2006,34 ( 3 ) : 209-219.
  • 10LIU Wei-min, LI Su-jian, ZHAO Fang-geng, et al. An ant colony optimization algorithm for the multiple travelling salesmen problem [ C ]//Proc of the 4th IEEE Conference on Industrial Electronics and Applications. 2009 : 1533-1537.

引证文献2

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部