Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (30): 54-56.DOI: 10.3778/j.issn.1002-8331.2010.30.016

• 研究、探讨 • Previous Articles     Next Articles

Continuous and colony optimization based on normal distribution model of pheromone

ZHAO Hai-ying,LI Gui-cheng,CUI Jun   

  1. School of Computer & Information Technology,Shanxi University,Taiyuan 030006,China
  • Received:2009-03-27 Revised:2009-05-18 Online:2010-10-21 Published:2010-10-21
  • Contact: ZHAO Hai-ying


赵海英,李桂成,崔 军   

  1. 山西大学 计算机与信息技术学院,太原 030006
  • 通讯作者: 赵海英

Abstract: The distribution of pheromone on the continuous space is simulated with Gaussian kernel.A random generator is used with this distribution as the state transition rule to choose the next point to move to,and pheromone is updated by adjusting parameters of the distribution according to the transitions of ant colony.Ants aggregate gradually around the optimal food source under the direction of pheromone.In order to get over the disadvantages of the slow convergence speed and stagnation behavior,a tabu search algorithm is inducted.And the results of the examples show that it can not easily run into the local optimum and can converge at the global optimum.

Key words: ant algorithm, normal distribution, continuous space optimization, tabu search

摘要: 以加权高斯函数模拟信息素的密度分布,并以此进行随机抽样,构成蚁群的状态转移规则。蚁群在信息素的引导下逐步向最优食物聚集。引入禁忌策略作为优进策略,以提高蚁群的寻优能力。测试表明算法适用于连续优化问题,能较快地找到函数的最优解。

关键词: 蚁群算法, 正态分布, 连续空间优化, 禁忌策略

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