Abstract:
Ant Colony System(ACS) can develop excellent performance via self-adaptive behavior. In order to find the internal rules of self- adaptive behavior, this paper introduces parameter-control and sets pheromone’s range, which are applied to the Traveling Salesman Problem(TSP). The ACS internal state is revealed via pheromone’s micro-control and statistical analysis of pheromone’s most values and distribution. Experimental results prove that the improved ACS does well in stability and searching solution.
Key words:
Ant Colony System(ACS),
self-adaptive,
parameter-control,
pheromone,
Travelling Salesman Problem(TSP)
摘要: 蚁群系统能够通过自适应调整不断优化算法的性能。为寻求算法自适应过程的内部规律,结合旅行商问题,采用参数控制、设置信息素范围的方法进行探讨。通过调控信息素的变化,以及对信息素最值、分布状态的统计分析,揭示算法优化过程的内部状态。实验表明,改进后的算法更稳定,问题解的搜索能力更强。
关键词:
蚁群系统,
自适应,
参数控制,
信息素,
旅行商问题
CLC Number:
LI Hua-feng; WU Wei; QIU Yi-ting; ZHONG Zhu-liang; ZHANG Jun. Improvement and Analysis of Self-adaptive Strategy in Ant Colony System[J]. Computer Engineering, 2009, 35(18): 194-197.
李华锋;吴 畏;丘一婷;钟柱亮;张 军. 蚁群系统自适应策略的改进与分析[J]. 计算机工程, 2009, 35(18): 194-197.