This paper considers the impact of the change in load capacity of hazardous materials transportation vehicle on the path risk, and establishes a new model to optimize the route of hazardous materials transportation vehicle, and makes decisions on the route of vehicle access demand points. Considering the dynamic change of load capacity and the delivery service time window, the optimization model of hazardous materials transportation path with minimum transportation distance, vehicle number and transportation risk is constructed. In this paper, a multi-objective evolutionary algorithm based on probability model is proposed. The algorithm uses the non-dominated sorting method of improved NSGA2 to select the population and solve the problem. Through Matlab simulation calculation, a case study was carried out on the dangerous goods transportation network data of 25 demand nodes. According to the different geographical distribution of transportation network nodes, the Pareto solution set obtained was analyzed in detail. The results show that the risk measurement method considering load capacity can provide diversified risk decision-making schemes to meet the different risk preferences of decision makers.

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