Research On Optimization Of China-EU Container Multimodal Transportation Route Based On Robust Optimization

With the One Belt One Road strategy put forward and continuously promoted,the economic and trade relationship between China and Europe are increasingly close,and the demand for logistics and transportation is booming,thereby promoting the continuous development and improvement of trade channels and transportation modes.Container multimodal transportation has ushered in unprecedented development opportunities with its advantages.However,due to its long-distance,wide area,and complicated operating procedures,China-EU container multimodal transportation is often affected by non-quantifiable factors,such as bad weather,vehicle mechanical failures,and changes in fuel rates,etc.It will cause large fluctuations in transportation cost,transportation time,and transhipment operation time,and then have a great impact on the choice of container multimodal transportation route and mode.Therefore,how to reduce the risk of uncertain factors on multimodal transport operators,choose the best transport route and transport mode for them,and then optimizing the container multimodal transport route from China 's inland cities to European hinterland cities has become a concern hot spot.This article starts from a reasonable and effective organization of container multimodal transportation and based on a comprehensive analysis of the existing container transportation corridors between China and Europe.Fully consider the random characteristics of transportation cost,transportation time,and transhipment operation time affected by a series of uncertain factors in reality,The robust optimization method is used to generate scene data by a random disturbance based on the baseline scenario data.At the same time,combining the reality of China-EU trade.A dual-objective container multimodal transportation plan selection model with minimum operation cost and operation time under the conditions of meeting carbon emission restrictions is established.Besides,this paper uses a non-dominated genetic algorithm with an elite strategy(NSGA-?)to solve the constructed dual-objective optimization model;Taking Nanjing-Berlin 20 40-foot container cargoes as an example,we conducted an empirical study on the selection of China-Europe container multimodal transportation route.In case of analysis:Firstly,CPLEX and NSGA-? algorithms are respectively used to solve small-scale calculation examples to verify the effectiveness of the model and algorithm;Secondly,the results of the single-objective model and multi-objective model are compared,it is proved that multi-objective optimization can solve the conflicts among various sub-objectives,and obtain a compromise solution of multiple objectives.Thirdly,the robust optimization model and the deterministic model are compared,and the disturbance method of scenario data is changed.It is proved that the robust optimization model is suitable for all scenarios,and the results are not sensitive to the weight coefficient,so it has better stability than the deterministic model.Finally,the sensitivity analysis of the carbon emission limit,operating time window,and regret value are carried out,to investigate the influence on the experimental results when they change.