Abstract

Aiming at the problem of matching logistics service supply and demand, this paper proposes a two-sided matching decision model of logistics service supply and demand based on the uncertain preference ordinal. In this model, the uncertain preference ordinal information is first expressed by the interval numbers of the logistics service supply and demand, and it is converted into the satisfaction degree of supply and demand matching uncertainty expressed by the interval number. Then, a multiobjective optimal matching model is constructed based on the largest overall satisfaction of the logistics service supply and demand side and the smallest satisfaction variance of the supply- and demand-side individual, and the multiobjective solution algorithm is designed based on nondominated sorting genetic algorithm-III (NSGA-III). Interval numbers are used to sort the matching results to obtain the approximately optimal two-sided matching scheme. Finally, this paper verifies the correctness of the model and validity of the algorithm.

Highlights

  • IntroductionTheory comes from life practice. We are making choices all the time, from the marriage matching choice of men and women to the choice of positions by university graduates, and we constantly choose in order to obtain satisfactory results for ourselves or the group, that is to say, where there is a choice, there is matching

  • As we all know, theory comes from life practice

  • This paper considers to express the uncertain preference information of the matching subjects of supply and demand of logistics service by the operation of interval numbers and turn it into uncertain satisfaction of supply and demand with the maximum overall uncertainty satisfaction of the supply side and the demand side of logistics service and the minimum individual uncertainty satisfaction variance of the supply side and the demand side, builds the multiobjective optimization model of two-sided matching of supply and demand of multi-to-multi logistics service based on uncertain preference ordinal, and designs the solving algorithm of the multiobjective model based on nondominated sorting genetic algorithm (NSGA)-III

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Summary

Introduction

Theory comes from life practice. We are making choices all the time, from the marriage matching choice of men and women to the choice of positions by university graduates, and we constantly choose in order to obtain satisfactory results for ourselves or the group, that is to say, where there is a choice, there is matching. Irdly, considering the uncertainty of individual preference ordinal information of supply and demand sides in reality, this paper uses interval number theory and interval number comparison method to clear the uncertainty problem and obtains effective calculation results to solve the two-sided matching problem of logistics service supply and demand, which makes the logistics service supply and demand problem more suitable for the actual needs.

Problem Description
Multiobjective Solution Algorithm Design
Solution Algorithm Based on NSGA-III
Analysis of Calculation Examples and Results
Objective 3 Objective 4
Conclusion and Future
Full Text
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