Optimization Research On Time And Cost Model Of Multimodal Transport Under Uncertain Environment

With the development of transportation technology, the expansion of the area ofeconomic activities, social competition is becoming increasingly fierce, the needs of themarket is no longer confined to the traditional single mode of transport, but a higherdemand on the logistics and transportation sector. The development needs, from thetransport demand side to the supply side, indicate that it needs an integrated transportsystem which makes different modes of transport working together, and it is themultimodal transport which can be able to meet the transportation needs of modernlogistics transportation. In the multimodal transport process, the key to multimodaltransport development is selecting the reasonable transport path and mode of transportto meet the needs of the users about the transport process time and cost, in order toachieve the transport of flexibility, convenience and reliability. However, due to thetechnical and economic characteristics of the different modes of transport,transportation time and costs have a benefit contradiction law. Therefore, seek thebalance point of interests of both parties to maximize co-benefits; thereby enhancing themarket competitiveness of intermodal transport has important social significance.In this paper, based on the intermodal transport virtual network graph and theanalysis of the uncertain factors existing in the process of multimodal transport,combined with the different transport needs of supply side and the demand side, thedual objective collaborative optimization model was constructed with the twooptimization objectives of transportation time and costs. The actual needs of multimodalorganization process, as the starting point of the establishment of the model, wasanalyzed firstly, and then list the factors influencing the process of multimodal transport,divided into certainties and uncertainties based on whether bringing the effects ofuncertainty to transport time, because of these uncertainties cannot be simplyrepresented by average number or random number, the article introduced fuzzy theoryto quantify them. Secondly, a multimodal transport network diagram was built, and onthis basis, we constructed a multimodal transport time-cost dual objective fuzzy pathoptimization model which has the optimization objectives of shortest transportationtime and the lowest cost. Due to the presence of triangular fuzzy number, the fuzzynumbers were transformed based on the theory of fuzzy chance constrainedprogramming model. Then, we designed algorithm of the multimodal transport time-cost model by use of the NSGAII genetic algorithm, and constructed a geneticalgorithm flowchart for this multi-objective mathematical problem. Finally, the thesisconstructs a multimodal simulation example in which the time and cost objectivefunctions have been optimized by using the Matlab program, a set of evenly distributedPareto optimal solution set was obtained, which provide decision makers with a widechoice of transport optimization.