带杂交算子的蚁群算法

An Ant Colony Algorithm with Crossover Operator

蚁群算法是一种由意大利学者等提出的新型模拟进化算法。它具有Macro Dorigo 许多优良性质,因此被广泛用于求解组合优化问题。但基本蚁群算法有许多不足。特别是它搜索速度慢,且容易陷入局部最优。该文针对这个问题提出了一种改进算法。该算法通过引入遗传算法中用到的杂交算子来改善蚁群,使其对应的问题的解更加优良。用改进算法求解TSP问题的结果表明改进算法是有效的。

Ant colony algorithm (ACA) is a new kind of simulated evolutionary algorithm. It is proposed by Italian scholar Macro Dorigo. Ant colony algorithm has many good features. So it was widely applied to complicate combinatorial optimization problems. But there is much deficiency. Specially, its searching speed is slow, and it is easy to fall in local best. An improved algorithm is presented to solve this problem. A crossover operator is contained in this algorithm. It is usually used in genetic algorithm. It can improve ant colony to make the corresponding solution better. The improved algorithm is applied to solve the traveling salesman problem(TSP). The result of the experiment suggests that the improved algorithm is effective.