Multimodal transport path selection method considering time value of goods under uncertain demand
To reduce the time value loss of high-value time-sensitive goods and rationalize multimodal transport paths,the influence of the time value of goods on multimodal transport path selection was investigated under uncertain transport demand.Based on the consideration of the value characteristics of the goods,a robust optimization model for multimodal transport paths was established by using the scenario analysis method in the robust optimization method with the objective of minimizing the combined transport cost,time value cost of goods and cost of carbon emission,and the constraints of hard time windows for nodal operations.According to the characteristics of the research problem,a Monte Carlo-based disaster adaptive genetic algorithm was adopted to discuss the model,and a combined transport network consisting of 15 urban nodes and three modes of transport-road,rail and waterway wee used as an arithmetic network for analysis.The results show that the rail distance as a percentage of the total transport distance increases by 17.28%for transport paths taking into account the time value of goods compared to those that do not,resulting in a 12-hour reduction in total transport time and a 16.19%saving in the time value cost of goods.As the average daily decay rate increasing,different transport paths will be chosen in different decay rate ranges.The increasing proportion of rail or road transport distance will be selected to improve transport timeliness and avoid the cost of the time value of goods rising too fast.The uncertainty of demand has increased transport cost,the cost of the time value of goods and the cost of carbon emission by 16.53%,3.44%and 17.31%respectively.Ultimately it can lead to a 9.65%increase in total transport costs.The results of the study can help decision makers estimate the demand and decay rate based on the actual demand situation and the nature of the goods,and provide a reference for their rational choice of transport paths to avoid excessive loss of time value of the goods.
multimodal transporttime value of goodspath selectionuncertain demandrobust optimization
万方数据
维普
