Study On Route Optimization Of Highway And Rail Combined Transportation Of Hazardous Materials In Random Environment

With the rapid development of social economy,human demand for hazardous materials,such as fireworks and medical alcohol,is increasing day by day,which brings great safety hazards during transportation.If you want to effectively avoid the risk,the effective measure is to coordinate the transportation of multiple modes of transport or route optimization.Through most scholars’ research,it is found that accidents are mostly caused by uncertain random factors,and it is difficult for traditional research methods to portray the uncertainties and random properties of transportation networks.Therefore,this thesis studies the uncertainties affecting transportation paths by studying the path optimization problem of public-rail intermodal transport of hazardous materials under deterministic conditions,and then combines theory of uncertainty to establish the intermodal transport of hazardous materials under stochastic environment.The path optimization problem has great practical research significance.Shippers have a clear demand for hazardous materials volume and time requirements,while most of the transport enterprises to pursue the lowest cost and risk;transport enterprises can reduce the number of delivery vehicles or shorten the delivery time as much as possible to reduce the total cost of transport,and transport risk and transport vehicle weight and the number of people affected by the pathway are related,that is,the more cargo transported,the greater the scope of the accident,the more injuries,the more serious the consequences of the accident,therefore,this study selects the container transport dangerous goods,as much as possible to reduce transport risk.This study established a multi-level transport network for intermodal transport of hazardous materials by public and railway based on an axial-spoke network and solves the topological connectivity problem;then establishes a hazardous materials path optimization model in a deterministic environment,and also establishes the lowest total transport cost,shortest total time and lowest total risk for many uncertain factors in the intermodal transport network of hazardous materials,such as risk value,customer time window,container capacity limit and transport in-transit time.The path optimization model of intermodal transportation of hazardous materials under stochastic environment is established.The solution is combined with the characteristics of intermodal transport of hazardous materials,and an improved hybrid intelligent algorithm combining stochastic simulation algorithm,neuronal network and genetic algorithm is designed,the core of which is to quote and improve the probability of adaptive adjustment of crossover and variation operators in NSGA-II algorithm.To verify the feasibility and efficiency of the model and algorithm,the Solomon benchmark test set is then solved,and the solution results are analyzed by parameter variation to show that:(1)the improved hybrid intelligence algorithm can solve the optimal solution more efficiently;(2)the selection of containers with large cargo capacity is beneficial to both transportation companies and risk control departments,which can reduce the total transportation risk and save costs;(3)the transportation en route The smaller the population density or the smaller the risk threshold will make the risk of transporting hazardous materials lower and the quality of the solved solution will become better;(4)paying the cost cost will lead to higher customer satisfaction and better timeliness;(5)the longer the transport time in transit,the higher the risk value may be.At the same time,it is also hoped that this study can provide theoretical support and diversified decision support for container transport enterprises and management in a complex transport environment.