车辆数不确定的软时间窗车辆路径问题的改进遗传算法

综合考虑车辆数和行驶距离两种优化目标，提出了VRPSTW的多目标优化模型，同时提出了解决VRPSTW问题的一种改进遗传算法。在算法中，通过适应度函浸透的变化，较好地解决了多目标优化的问题；通过对交叉算子改进，增加了算法的寻优能力，同时又克服了算法对群体多样性的要求；针对遗传算法局部搜索能力弱的问题。加入了2-opt局部搜索方法，很好地弥补了遗传算法的不足。经过实验，本方法能较好地解决VRPSTW问题，从而对运榆决策提供有力支持。

Improved Genetic Algorithm for Variable Fleet Vehicle Routing Problem with Soft Time Window

Vehicle Routing Problem with Time Windows(VRPTW)is represented as a multi-objective optimization problem, both considering number of vehicles and total cost(distance)and simultaneously propose a improved genetic algorithm to resolve this problem. In the algorithm, we resolve the balance of the two objectives through fitness function; and by using the improved Cross-Over operation, we can not only increase search ability of the algorithm, but also get rid of the limit of diversity of population; adding 2-opt in the algorithm because of the lack of local search ability of Genetic Algorithm to increase the local search ability of the algorithm. The experiment result indicates that the algorithm is efficient for VRPSTW and can provide useful support to make decision.