解旅行商问题的混沌蚁群算法

Solving Traveling Salesman Problem by Chaos Ant Colony Optimization Algorithm

利用混沌运动的遍历性、随机性和规律性等特点,提出了一种求解旅行商问题的混沌蚁群(CACO)算法.该算法的思想是采用混沌初始化进行改善个体质量和利用混沌扰动避免搜索过程陷入局部极值.与模拟退火算法、标准遗传算法进行比较,仿真结果表明该方法是一种简单有效的算法.

By use of the properties of ergodicity, randomicity, and regularity of chaos, a chaos ant colony optimization （CACO） algorithm is proposed to solve traveling salesman problem. The basic principle of CPSO algorithm is that chaos initialization is adopted to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local optimum. Compared with the standard GA and simulated annealing algorithm , simulation results show that chaos ant colony optimization is a simple and effective algorithm.