具有模糊旅行时间的VRP的一种混合遗传算法

A Hybrid Genetic Algorithm to the Vehicle Routing Problem with Fuzzy Traveling Time

传统确定性车辆路径问题是近几十年来运筹学领域研究的一个热点问题。但在许多实际的应用中,由于受客观世界中存在的不确定性因素以及人类观察、认识事物的模糊性的影响,车辆路径问题的某些参数可能是模糊的、不确定的。文中传统确定性车辆路径问题被扩展为具有模糊特征的模糊车辆路径问题。在对具有模糊旅行时间的车辆路径问题进行简单描述的基础上,构建了该问题的数学模型,并通过将模糊逻辑、模糊控制方法与传统车辆路径问题的遗传算法进行有效结合,提出了解决该问题的一种混合遗传算法。最后给出了该问题的一个计算实例,并通过随机模拟试验验证了该算法的有效性和优越性。

The traditional deterministic ＇vehicle routing problem （VRP） is one of the most important and difficult problems in operational research filed in the past many decades. But in many practices, due to the uncertain factors existed in the world and the fuzziness of human being, many parameters of VRP are uncertain or fuzzy. In this paper, the traditional deterministic VRP is expanded to the situation that the VRP has fuzzy features. The traveling time of the VRP are treated as fuzzy uumbers in this paper. After a simple description of the VRP with fuzzy traveling time, a mathematical model for the problem is built. Then, a hybrid genetic algorithm to this kind of vehicle scheduling problem is developed based on the effective combination of the genetic algorithm and fuzzy logistic method. Finally, an example is presented, and the validity and superiority of the algorithms are validated by simulation.