Study on Multi-requirement Points Vehicle Scheduling Model and Its Swarm Mix Algorithm
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摘要: 建立货运关系明细的多需求点车辆调度模型, 模型求解过程是先由粒子群算法的粒子位置向量得到单车运送的货物, 再由蚁群算法优化单车路径, 根据优化目标筛选粒子, 直到终止条件, 实现所有货物对所有车辆的分配. 实例求解结果表明混合求解得到的车辆总路径小于蚁群算法得到的结果.
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关键词:
- 多需求点 /
- 车辆调度问题(VSP) /
- 粒子群算法(PSO) /
- 蚁群算法(ACO)
Abstract: Multi-requirement points vehicle scheduling models (MRP-VSM) with detailed freight relation were established. The model optimization course is as follows: first assign freights to vehicles by particle position vector, then get single vehicle's route by ant colony optimization (ACO), filtrate particles by optimization aim, circulate until terminate qualification is met. Swarm mix algorithm can assign all freights to all vehicles. Illustration result shows the optimization vehicle route length by swarm mix algorithm is less than modified ACO.
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