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针对危险品车辆路径问题中车辆访问多个需求点的特性,在风险度量方式上考虑了运输过程中车辆载重量变化,建立了最小化总运输距离以及最小化总运输风险的双目标优化模型.采用改进的蚁群算法对模型进行求解并获得优化问题的非支配解,数值实验说明改进的风险度量方式更适合于危险化学品车辆路径问题,改进的蚁群算法能够有效率地对模型进行求解.
Aiming at the characteristics of vehicle access to multiple demand points in the vehicle routing problem of dangerous goods, the change of vehicle load in the process of transportation is taken into account in the risk measurement method. A two-objective optimization model is established to minimize the total transport distance and minimize the total transport risk. The improved ant colony algorithm is used to solve the model and to obtain the non-dominated solution to the optimization problem. The numerical experiments show that the improved risk measurement method is more suitable for the hazardous chemicals vehicle routing problem. The improved ant colony algorithm can efficiently solve the model .