| China’s highway freight volume has always occupied the main position of the total freight volume,and the development of the highway freight industry is very important for the entire freight industry and even the development of the logistics industry.However,the traditional road freight industry has a large group of individual retail investors,with a large number of idle transportation capacity,and there are basic problems of "hard to find vehicles" and "hard to find vehicles".Highway freight is seeking intelligent transformation.Due to its reliance on high-tech technologies such as the Internet,big data,and artificial intelligence,the vehicle cargo matching platform can integrate and accurately match scattered transportation capacity and cargo sources,thereby reducing costs and increasing efficiency,gradually becoming the main operating mode of the highway freight industry.Under the guidance and support of national policies,the vehicle cargo matching platform is gradually becoming standardized and developing rapidly.However,the vehicle cargo matching platform is still in its early stages of development,with problems such as low quality of vehicle cargo matching results and poor customer experience.This has resulted in a decrease in the user stickiness of the vehicle cargo matching platform and restricted the good development of highway freight transportation.For this reason,this article introduces the hesitant fuzzy term(HFLTS)to describe the preference evaluation between the cargo owner and the vehicle owner in a complex and uncertain environment.When conducting vehicle cargo matching,the goal is not only to maximize satisfaction,but also to consider the willingness of both parties to match.It aims to comprehensively and realistically describe the satisfaction of both vehicle and cargo parties and match better solutions.Through combing the relevant concepts and theoretical basis,a hesitant fuzzy multicriteria satisfaction measurement method based on HFLTS is designed.The indicators are divided into expectation indicators,attribute indicators,and trust indicators,among which expectation indicators and trust indicators participate in the measurement of satisfaction.Expected index satisfaction is measured by a utility function,while trust index satisfaction is measured by a hesitant fuzzy multi criterion method.An improved normalization method based on HFLTS is used to standardize trust index satisfaction,and then aggregated with expected indicators.The weight of each indicator participating in the satisfaction aggregation is determined through the coefficient of variation method,which is more objective and directly calculated based on existing data information.Aggregate the satisfaction of each indicator with the weight of each indicator to obtain the overall satisfaction of the owner and the vehicle owner with each other.Further,based on the characteristics of the problem of vehicle cargo matching and less-than-truckload vehicle cargo matching,through condition screening and introducing matching intention,the optimization models for single objective bilateral one-to-one vehicle matching and single objective bilateral one-to-many less-than-truckload vehicle matching were constructed,and numerical examples were analyzed.In a vehicle cargo matching example,the overall satisfaction of the scheme obtained by the method in this thesis is reduced by0.5% compared to the minimax method and the simple linear weighting method,but the difference value is reduced by 52.2%.The difference value is a direct manifestation of the stability of the matching scheme.Therefore,the matching scheme obtained by the method in this thesis greatly increases the stability of the matching scheme when the overall satisfaction decreases slightly,and is generally more excellent.In an example of less-than-truckload truck cargo matching,the overall satisfaction of the solution obtained in this thesis is the same as that obtained by the minimax method and the simple linear weighting method,both of which are 9.82,but the difference value is somewhat reduced.It is proved that the method in this thesis is also applicable and effective in the matching of less-than-truck vehicles and goods.Finally,a summary of the full text of the study and analysis of several possible research directions are presented. |
