基于遗传蚁群算法的带时间窗多车场车辆调度问题

Study on Multi-distribution Vehicle Scheduling with Time Window Based on Genetic Algorithm-ant Colony Algorithm

给出带单边硬时间窗的多车场车辆调度问题的数学模型,并提出一种遗传蚁群融合算法。该算法在遗传算法的基础上加入蚁群路径搜索和自适交叉变异来提高算法搜索能力,并且采用模拟退火个体接受方式接受蚁群路径搜索产生的新个体,从而使算法提高了跳出局部最优点能力。结合算例计算验证了算法的有效性和正确性。

The multi-distribution centers vehicle scheduling model with a single time window was built in this paper. A new hybrid algorithm combining Ant colony algorithm with genetic algorithm was proposed. In order to improve the Search ability of the algorithm,a colony algorithm and a adaptive for adjusting and mutation probability were combined based on the genetic algorithm. To improve the ability of algorithm to avoid being premature,a way with Simulated annealing algorithm was utilized to accept new member produced by Ant colony algorithm. Finally,the effectiveness and validity of the algorithm were tested through simulation.