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一种连续空间优化问题的蚁群算法及应用 被引量：12

Ant Colony Algorithm in Continuous Space
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摘要 针对随机优化算法收敛困难及搜索时间较长的问题,提出一种求解连续空间优化问题的蚁群算法,为蚁群算法在连续空间中的应用提供了一个可行的方案。给出了该算法的详细定义及实现步骤,并将该算法应用于多变量函数优化及热工控制系统控制器参数优化,仿真结果表明:该算法具有良好的全局优化性能,能加快收敛速率,解决了随机优化算法收敛困难的问题,并提高寻优精度。 Ant colony algorithm is a novel simulated evolutionary algorithm.Preliminary studies have showed that it has many promising futures.Based on the ant colony optimization idea,a new algorithm for continuous optimization problem is presented.The ant＇s moving direction and step are determined by the best result of last generation.The ant who has found the best way in last cycle will search for a new result in a certain area.The pheromone will be updated after a cycle.Typical examples indicate the better performance of the proposed algorithm.
作者 孙学勤 刘丽 付萍 王学厚
机构地区 云南电力集团有限公司 华北电力大学自动化系
出处 《计算机工程与应用》 CSCD 北大核心 2005年第34期217-220,共4页 Computer Engineering and Applications
关键词 蚁群算法 连续空间优化 PID参数优化 ant colony algorithm,continuous optimization,PID controller optimization
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献7

  • 1[1]Dorigo M ,Gambardella LM.Ant colony system;A cooperative learning approach to the travelling salesman problem[J].IEEE Trans on Evolution Computation,1997; 1 (1) :53～66
  • 2[2]Dorigo M,Maniezzo V,colony A.Ant system;Optimazation by a colony of cooperation agents[J].IEEE Trans on SMC;part B,1996;26(1):29～41
  • 3[3]Colorni A,Dorigo M,Maniezzo V et al.Ant system for job-shop scheduling[J].Belgian J Oper Res Stat Comp Sci,1994;34:39～53
  • 4高尚,钟娟,莫述军.连续优化问题的蚁群算法研究[J].微机发展,2003,13(1):21-22. 被引量：77
  • 5汪镭,吴启迪.蚁群算法在连续空间寻优问题求解中的应用[J].控制与决策,2003,18(1):45-48. 被引量：100
  • 6[6]Maniezzo V,Colorni A.The ant system applied to the quadratic assignment problem[J].IEEE Trans on Knowl Data Eng,1999; 1 (5):769～798
  • 7[7]Barkaoui K.Verification inconcurrent Programming with Petri nets structural technique[C].In:Proc of the 3rd Int IEEE High Assur Syst Eng Symp,1998:124～133

二级参考文献16

  • 1马振华 刘坤林 等.运筹学与最优化理论卷[M].北京:清华大学出版社,1998.254-278.
  • 2[1]Dorigo M, Gambardella L M. Ant colony system: A cooperative learning approach to the travelling salesman problem[J]. IEEE Trans Evol Comp,1997,1(1):53-66.
  • 3[2]Dorigo M, Maniezzo V, Colorni A. Ant system: Optimization by a colony of cooperating agents[J]. IEEE Trans SMC: Part B,1996,26(1):29-41.
  • 4[3]Gambardella L M, Dorigo M. Solving symmetric and asymmetric TSPs by ant colonies[A]. Proc IEEE Int Conf Evol Comp[C]. Piscataway, 1996.622-627.
  • 5[4]Boryczka U, Boryczka M. Generative policies in ant systems for scheduling[A]. 6th European Congr Intell Tech Soft Comp[C]. Bruxelles,1998.1:382-386.
  • 6[5]Boryczka U. Learning with delayed rewards in ant sys-tems for the job-shop scheduling problem[A]. First Int Conf Rough Sets Current Trends Comp[C]. Bruxelles,1998.271-274.
  • 7[6]Gambardella L M, Taillard E D, Dorigo M. Ant colonies for the quadratic assignment problem[J]. J Oper Res Soci,1999,50(2):167-176.
  • 8[7]Maniezzo V,Dorigo M,Colorni A.Algodesk:An experimental comparison of eight evolutionary heuristics applied to the quadratic assignment problem[J]. European J Oper Res,1995,81(1):188-204.
  • 9[8]Maniezzo V. Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem[J]. Infor J Comp,1999,11(4):358-369.
  • 10[9]Maniezzo V, Colorni A. Ant system applied to the quadratic assignment problem[J]. IEEE Trans Knowl Data Eng,1999,11(5):769-778.

共引文献154

同被引文献85

引证文献12

二级引证文献118

计算机工程与应用
2005年 第34期

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