基于混合蚁群算法的物流配送路径优化

基本蚁群算法在优化过程中存在搜索时间长、易陷入局部最优解的缺点.研究构造了一种基于蚁群算法的混合算法,利用蚁群算法首先求出问题的基本可行解,采用遗传变异中的单亲逆转算子进行再次优化,求得问题最优解.对物流配送路径优化的仿真试验表明,相对于基本蚁群算法和遗传算法,混合算法的优化质量和效率更优.

Optimizing route of logistics based on hybrid ant colony algorithm

Ant colony algorithm (ACA) is successfully applied to several combinatorial optimization problems, but it has some short-comings such as its slow computing speed, and it is easy to fall in a local optimal. So a hybrid ant colony algorithm is proposed by using the standard genetic algorithm (GA) in optimizing the ACA parameters. The basic feasible solution is searched by ACA firstly, thegn the quadratic optimal is gotten by using single-parent reverse mutation operators of GA, finally obtaining is fit for the problem optimal solution by comparison. The algorithm is applied on the logistics delivery routes problem, the simulation results showed that its optimi-zation quality and efficiency superior to the traditional ACA and the GA.