摘要
传统蚁群算法在求解中容易出现搜索时间长、收敛过早或停滞现象,为克服这些缺点,通过对蚁群算法进行选择策略、信息素更新等方面的改进,以加快算法的收敛速度,提高算法的搜索能力。再将改进后的蚁群算法引入物流运输车辆调度、综合车辆调度理论,对物流运输车辆的优化调度进行了探讨,对有时间窗车辆调度问题(VSPTW)探求新的求解方法,运用Matlab语言进行编程实现,应用实例对算法进行验证。实践证明,改进后的蚁群算法基本上克服了一般蚁群算法自身的不足,提高了算法的性能。
Long time ,premature convergence or stagnation may be arised in the traditional ACA for solving the search. I in order to overcome these shortcomings,this paper makes improvements by ACA selection strategy and pheromone updating improvements to speed up the convergence rate and improve the algorithm＇s search ability. This paper introduces the im-proved ACA to solve vehicles scheduling problems, integrated vehicle scheduling theory, the optimal operation of logistics transport vehicles was discussed, and, explore the new method to solve the Vechile Scheduling Problem with Time Window （VSPTW） , use matlab language for programming, then examples to verify the algorithm. Proved that, the improved ACA is basically ACA to overcome the general lack of its own to improve the performance of the algorithm.
出处
《江南大学学报（自然科学版）》
CAS
2012年第3期273-276,共4页
Joural of Jiangnan University (Natural Science Edition)
基金
国家自然科学基金项目(70771030)
关键词
蚁群算法
物流运输
车辆调度优化
时间窗
Ant Colony Algorithms
Physical Transportation
Vehicle Routing Optimization Time-window
