
基于模拟植物生长算法的车辆调度问题
Vehicle scheduling problem based on plant growth simulation algorithm
基于配送企业车辆资源的限制和客户需求时间窗的要求, 在考虑外包车辆和配送人员加班的情况下, 对带时间窗的车辆调度问题进行扩展研究. 根据客户需求的随机性特点构建以最小化车辆配送总成本为目标的机会约束规划模型, 并设计求解该问题的模拟植物生长算法. 结合车辆调度具体实例, 将模拟植物生长算法与遗传算法进行比较, 结果表明该算法不仅可以获得最优解, 而且提高了求解效率, 是一种有效的方法.
Based on the limit of the distribution enterprises' vehicle resource and the demand of customers' time windows, the paper gives an extensive research on the vehicle scheduling problem with time windows, which considers the situation of using outsourced vehicles and overtime for drivers. According to the stochastic demand of the customers, a chance-constrained program model was bulit to optimize the total cost of vehicle scheduling problem. A solution method-plant growth simulation algorithm (PGSA) is presented. Then, by means of calculating of the example and comparing with genetic algorithm, the results show that the optimum can be reached, meanwhile the efficiency of the presented algorithm is better than the genetic algorithm.
车辆调度 / 外包车辆 / 加班 / 模拟植物生长算法 {{custom_keyword}} /
vehicle scheduling / outsourcing vehicle / overtime / plant growth simulation algorithm {{custom_keyword}} /
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国家自然科学基金(61375003); 河北省自然科学基金(F2014402040); 河北省教育厅人文社会科学研究重大课题攻关项目(ZD201442)
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