基于改进蚁群算法的双向物流路径优化

针对物流路径优化已有算法运算过程复杂、精度不高、过早收敛等问题,对蚁群算法进行了改进,以解决物流路径优化问题.为了消除蚁群算法的易停滞、收敛慢等问题,从蚂蚁转移策略、信息素更新方式以及遗传算法的融合等方面对算法进行了改进.针对双向物流的路径优化问题,通过增加启发函数、设计转移策略等方面来改进蚁群算法,使得算法能更好地考虑综合因素来进行搜索,能够更全面、更准确地找到合适的下一节点,从而得到更优的路线.

Logistics Routing Optimization Based on Improved Ant Colony Algorithm

Due to computation complexity, lower accuracy and premature convergence of the conventional algorithm, the ant colony algorithm was improved to solve the routing problem of logistics. In order to eliminate the problems that ant colony algorithm is easy to be stagnant and its convergence is slow, the algorithm was improved including the following points such as the transfer strategies of the ants, the pheromone update method and the integration of genetic algorithm. To solve the path optimization of simultaneous delivery and pickup, the heuristic function was added and the transfer strategies were designed, which made the algorithm conduct a search by considering a combination of factors reasonably, and could find the next right point more comprehensively and more accurately, then, a better path could be gotten.