基于TOPSIS的犹豫模糊元偏好下的双边匹配决策方法

Two-sided Matching Decision-making Method with Hesitant Fuzzy Element Preference Based on TOPSIS

双边匹配理论方法广泛应用在各个行业与日常生活中,产生较大的经济价值与社会价值。然而,现实双边匹配决策过程中,决策问题的复杂性使得双方主体给出的偏好信息是模糊的,决策环境的复杂性可能使所给出的偏好信息是不确定的。考虑到现实双边匹配问题的上述特征,给出一种新的犹豫模糊元偏好下的双边匹配决策方法。首先,基于TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)方法将犹豫模糊元矩阵转化为贴近度矩阵,即主体满意度矩阵;接着,构建以双边主体满意度最大化为目标的多目标规划模型;进一步地,运用线性加权法将多目标规划模型转化为单目标规划模型,并求解该模型得到最佳双边匹配方案;最后,使用一个人岗匹配实例验证该模型的有效性与有效性。

The theory and method of two-sided matching has discovered extensive utilization across diverse sectors and daily existence,yielding significant economic and societal worth.It expedites the procedure of pairing two subjects contingent upon their inclinations,be it job seekers and employers,students and universities,or buyers and sellers.Nevertheless,the decision-making milieu within authentic two-sided matching procedures is frequently intricate,ensuing in the absence of preference data from both sides.Additionally,the inherent indeterminacy of decision-making augments the ambiguity of the furnished preference information.To tackle these practical scenarios in the realm of two-sided matching research,a proposition novel two-sided matching decision-making method on hesitant fuzzy element information is proposed in this paper.Primarily,the problem of one-to-one two-sided matching based on hesitant fuzzy elements is expounded,thus enabling a more adaptable representation of preferences.Through these hesitant fuzzy elements,the uncertainty and ambiguity inherent in decision-making are aptly captured,allowing decision-makers to convey their preferences as a spectrum of possibilities rather than rigid values.Subsequently,the technique known as Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)is employed to extract the satisfaction levels of decision-makers.Secondly,the TOPSIS method is used to calculate subject satisfaction.By normalizing the hesitant fuzzy elements information provided by two-sided subjects,the distance between each alternative solution and the ideal solution is calculated,and based on this,the subject satisfaction is obtained.The applied satisfaction calculation method effectively enhances the description of two-sided subject preferences.By normalizing the hesitant fuzzy element information provided by both parties and determining the relative proximity of each alternative to the ideal solution,this method enhances the evaluation of preferences,accounting for multiple criteria and the accompanying uncertainty.Moreover,this approach takes into consideration the constraints of one-to-one matching and establishes a multi-objective programming model for two-sided matching.This model incorporates the satisfaction levels of decision-makers,the matching constraints,and the imperative of equity,all while determining the optimal solution to the two-sided matching conundrum.Recognizing the relative significance of diverse criteria in the process of matching decision-making,a linear weighted method is employed to surmount the model.To assert the dependability and soundness of the proposed approach,a case study on the pairing of personnel with jobs has been conducted.The research findings elucidate that the tool for representational rendering of fuzzy information,comprised of hesitant fuzzy elements,proficiently articulates the information for preference evaluation furnished by two-sided subjects amidst intricate circumstances.The method put forth triumphantly resolves the quandary of decision-making in two-sided matching within an environment pervaded by hesitant fuzzy preferences.The outcome of comparative analysis reveals that the amalgamation of a positive ideal solution and a negative ideal solution effectively upholds the equity of the resultant matching solution and facilitates the formation of gratifying matching resolutions.By taking into consideration both fairness and diversification of information,the proposed approach to decision-making augments the perks of two-sided matching platforms and enhances matching efficacy.This research enhances the already extensive corpus of literature on decision-making methodologies for two-sided matching within intricate contexts.The proposed approach to decision-making takes into account the equitability of both subjects,the variegation of information,and the indeterminacy of preferences,thereby furnishing a foundation for bolstering the advantages of two-sided matching platforms and refining matching efficiency.In addition,this research effectively advances the application understanding of the theoretical framework of fuzzy-based two-sided matching in decision-making processes.It also holds potential practical value across multiple industries,including job recruitment,university admissions,and online marketplace platforms.