模糊需求信息条件下的车辆路径问题研究

Research of vehicle routing problem under condition of fuzzy demand

在对模糊需求信息条件下的车辆路径问题进行简单描述的基础上,通过引入决策者主观偏好的概念,提出了解决该问题的一种基于模糊可能性的混合遗传算法.同时,在最小化车辆使用数与车辆行驶距离的目标下,通过随机模拟方法研究了决策者的主观偏好对最终决策目标的影响作用,并通过与其它计算方法的比较证明了基于模糊可能性的混合遗传算法的优越性.

The vehicle routing problem with one depot from which vehicles deport and to which they return after completing their service is considered. The quantities to be picked up at the nodes are assumed to be only approximately known. The paper develops a model to design vehicle routings of this kind of vehicle routing problem on the basis of the introduction of the concept of the decisionmaker's preference. The model is based on the genetic algorithm and the rules of fuzzy mathematics. Finally, the influence of the decisionmaker's preference on the final objective of the problem is discussed using the method of stochastic simulation, and the effectiveness of the hybrid genetic algorithms is demonstrated.