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中文摘要：
以运输费用最小为目标，在考虑客户服务优先级和车辆装载率等约束条件下，构建了单车场单车型联合运输车辆路径问题模型和单车场多车型单点配送多趟服务车辆路径问题模型，并用改进的扫描算法和改进的遗传算法进行求解，最后，将郑州煤电物资供销有限公司的物资配送作为案例进行研究，从运输费用、运输里程和服务优先级三方面评价改进的扫描算法和改进的遗传算法的求解结果，得到在车辆装载率相同的情况下，两者各有所侧重：改进的遗传算法所求得的最优解在运输费用和配送里程上都优于改进的扫描算法，而改进的扫描算法则最大程度地保证了客户的服务优先级。
英文摘要：
To minimize the delivering cost, we build a single-depot combined delivering vehicle routing problem model and a single-depot point to-point delivering vehicle routing problem model,considering the constraints on the customers~ service priorities and the full load rate of vehicles. We then present an im- proved sweeping algorithm and improved genetic algorithm to solve the mathematical models. We also study vehicle routing problem for Zhengzhou Coal Electricity Material Supply and Marketing Limited Com- pany, evaluate the solutions in terms of delivery cost, delivery distance and full load rate of vehicles. The results show that, in the situation with the same full load rate of the vehicles, the best solution of the improved ge- netic algorithm is better than that of the improved sweeping algorithm in terms of delivery cost and delivery dis- tance However, the improved sweeping algorithm provides guarantee for the service priority.
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