Study On Optimization Of Multimodal Container Transportation Path Under Uncertain Environment

The exchanges and development of economy and trade have promoted transportation to be green and environmentally friendly,putting forward new requirements for the sustainable development of transportation modes.The purpose of studying multimodal transport path optimization is to arrange transport modes rationally,ameliorate unreasonable phenomena in current transport,and reduce transport costs,so as to achieve the purpose of reducing costs and increasing efficiency.Particularly,the development of multimodal transport with railway participation,can improve the utilization rate of railway freight,which is of great significance to improve the low occupancy of railway container freight and the efficiency of multimodal transport.With the carrier of container,the paper studies multi-objective path optimization of multimodal transport with railway participation,which takes fuzzy time into consideration.The paper mainly includes the following contents:(1)The paper sorts out the theory of multimodal transport network modeling,including mastering the definition and basic characteristics of multimodal transport,familiar with the basic organization form and operation flow of multimodal transport,and understanding the construction method of multimodal transport network model.(2)The paper,with railway participation,analyzes the impact of time and space constraints(time windows and transport capacity)on multimodal transport.Taking the minimum costs as the objective,the single-task path optimization model with mixed time window constraints,and the multi-task path optimization model with transport capacity constraints are established,respectively.The chicken swarm algorithm(CSO)is used to solve models respectively.The results show that both time window constraints model and the transport capacity constraint model can solve the optimal solution.Moreover,time windows and transport capacity can affect transport schemes and transport costs.(3)The paper constructs and clarifies the multi-objective path optimization model with fuzzy time.According to the uncertainty of multimodal transport process,transport time and transit time are regarded as uncertain variables,represented by triangular fuzzy number.Taking cost,time and carbon emission minimization as objectives,a multi-objective path optimization model considering fuzzy time is constructed,with time windows and transport capacity as constraints.For fuzzy variables,an opportunity constrained programming model is used to obtain a clear multi-objective path optimization model with fuzzy time.(4)The paper solves the multi-objective path optimization model considering fuzzy time.Based on the non-dominated sorting genetic algorithm with elite strategy(NS GA-II),the hybrid algorithm DE-NSGAII is designed in which the mutation and crossover strategies of differential evolution algorithm(DE)are introduced and an adaptive scaling strategy is proposed.The multi-objective path optimization model considering fuzzy time is solved,and the solution obtains a uniformly distributed Pareto solution set,which verifies the validity of the model and algorithm,and provides a series of transportation solutions for operators to choose.In the multimodal transport organization,giving full play to the advantages of different modes of transport scientifically,planning transportation routes and modes and rationally,will play a good role in realizing the purpose of reducing costs and increasing efficiency to build a more efficient and perfect comprehensive transport system.