Study On The Route Optimization Considering Schedule Limits Of Multimodal Transport Of Goods

With the development of China's transportation network structure,and the completion of the integrated hub,multimodal transport is developing rapidly,and is also more and more welcomed by logistics enterprises.However,there are many problems in multimodal transport,such as low efficiency,low timeliness,low information and so on.In order to further promote the rapid development of multimodal transport,breaking through these bottlenecks is imperative.In the actual process of multimodal transport of goods transport,transport routes and transport choice are the key factors that affect the optimal transport path is obtained,including transportation costs,transportation time,transportation risk is decided whether the whole multimodal transport service level determinants of the consignment requirements of enterprises.This paper will schedule constraints considering multimodal transport path optimization research,path optimization model is extended into consideration limited schedule optimization of multimodal transport of goods,and according to the actual situation design of genetic algorithm to solve the model.The main contents of this paper are as follows:a)Access to a large number of consolidation in recent years and the related literature on multimodal transport,multimodal transport infrastructure work as well as the domestic and foreign research situation analysis,pointed out the shortcomings of current research,put forward research direction and in the same;b)Analysis of multimodal transport path optimization factors,and put forward to the transportation cost,transportation time,transportation risk as the optimization objective function of the original model of multimodal transport path,detailed schedule restrictions in the model describe the idea,then the original optimization model is extended to consider limiting the schedule of multimodal transport optimization model;c)The model of transportation cost,transportation time,transportation risk three objective function for 1 dimensional processing,and multiplied by the corresponding weight coefficient,compared with the single objective model can do better in general the optimal path to meet customer decision between transportation cost,transportation time,transportation risk three on demand;d)On the basis of the analysis and design of multimodal transportation network,a genetic algorithm based optimization method for multimodal transportation route optimization is designed.Detail to determine the transport factor weights with analytical hierarchy process,and determine the general goods using this method,fragile and tide goods,fresh,frozen in the objective function of multimodal transport of goods transport costs,transport time and transport method of weight coefficient;e)To entrust the third party logistics enterprises will be a group of 200 tons of general cargo from Chongqing to Shanghai as an example,the use of genetic algorithm does not consider the schedule constraints and consider two models(i.e.schedule constraints the original model and the extended optimization model)are solved,and the results are analyzed.According to the result of the analysis can be found,city nodes,ships and other modes of transport train fixed class time has great influence on the choice of the optimal path,the schedule constraints considering multimodal transport path optimization model,logistics enterprises can get more reasonable transportation plan.The main points of this paper are as follows:a)In this paper the establishment of multimodal transport path optimization of the original model,the fusion coefficient and risk factor to offset the damage which is different from the past simple accident probability quantitative risk degree;b)This article from the actual situation of multimodal transport,the schedule constraints and damage coefficient considering the original model of path optimization of multimodal transport,make the model more fit the actual situation;c)In this paper,we first analyze multimodal transport network,and then coding,which can reduce the coding difficulty and shorten the running time of the program.