基于交通流量控制的二元蚁群优化模型

Binary Ant Colony Optimization Based on Traffic Flow Control

针对多模域上的蚁群优化,提出了一种交通流量控制策略。此策略启发于由A.Dussutour等发现的真实蚁群在高度拥挤下的交通组织行为。算法引入了“交通流量控制”策略来保持群体的多样性,对于每段路径都引入相应的流量阈值。算法被应用于几个典型多模函数优化中并与二元蚁群优化、二元菁英蚁群优化和二元蚁群系统算法进行比较。实验结果证明基于交通流量控制的二元蚁群优化算法能够在多模域中获得稳定的全局和局部峰值集,拥有远优于上述算法的多模搜索能力。

A Traffic Flow Control strategy for Binary Ant System （TFC-BAS） was proposed and applied to multimodal optimization problems. The strategy is inspired by traffic organization in real ants under crowded conditions found by A, Dussutour et, al, The strategy can prevent loss of diversity of solutions by introducing a so called ＂flow thresholar＇ to each path of solutions, Experiment results on some typical multimodal complex functions show that TFC-BAS has much better capability than Binary Ant System （BAS）, Binary Elitist Strategy for Ant System （E-BAS） and Binary Ant colony System （BACS） in locating and marinating stable global arid local optima in multimodal search space.