摘要
针对一般的 (无约束或有约束 )函数优化问题 ,给出一种新的基于蚂蚁群集智能的随机搜索算法 ,对目标函数没有任何可微甚至连续的要求 ,可有效克服经典算法易于陷入局部最优解的常见弊病。大量算例测试结果表明 。
Based on the swarm intelligence of ants, a new stochastic searching algorithm for the general (constrained or unconstrained) function optimization is presented. The proposed algorithm requires no prerequisites of differentiation or even continuation of objective function, and can effectively overcome thecommonlyseendisadvantageofgettinginto local optimum by classical algorithm. Numerical experiments show the good performance of the algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2002年第B11期719-722,726,共5页
Control and Decision
基金
上海市曙光计划基金项目 (2 0 0 0 SG30 )
