Strategyproof Mechanism for Two-Sided Matching with Resource Allocation

Liu, Kwei-guu; Yahiro, Kentaro; Yokoo, Makoto

doi:10.1016/j.artint.2023.103855

Cited by 6 publications

(2 citation statements)

References 58 publications

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“…Furthermore, diversity constraints ensure a balanced mix of different student types within a school [8][9][10][11][12]. This topic has been receiving increased attention from AI researchers [13][14][15][16][17]. Throughout this paper, we focus on the context of a school-student allocation problem to enhance reader comprehension, although the results are applicable to general allocation problems.…”

Section: Introductionmentioning

confidence: 99%

Strategyproof and fair matching mechanism for union of symmetric m-convex constraints

Barrot,

Yahiro,

Yokoo

et al. 2024

PLoS ONE

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We identify a new class of distributional constraints defined as a union of symmetric M-convex sets, which can represent a wide range of real-life constraints in two-sided matching settings. Since M-convexity is not closed under union, a union of symmetric M-convex sets does not belong to this well-behaved class of constraints. Consequently, devising a fair and strategyproof mechanism to handle this new class is challenging. We present a novel mechanism for it called Quota Reduction Deferred Acceptance (QRDA), which repeatedly applies the standard Deferred Acceptance mechanism by sequentially reducing artificially introduced maximum quotas. We show that QRDA is fair and strategyproof when handling a union of symmetric M-convex sets, which extends previous results obtained for a subclass of the union of symmetric M-convex sets: ratio constraints. QRDA always yields a weakly better matching for students than a baseline mechanism called Artificial Cap Deferred Acceptance (ACDA). We also experimentally show that QRDA outperforms ACDA in terms of nonwastefulness.

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Section: Introductionmentioning

confidence: 99%

Strategyproof and fair matching mechanism for union of symmetric m-convex constraints

Barrot,

Yahiro,

Yokoo

et al. 2024

PLoS ONE

Self Cite

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“…Li Yingxin et al [10] studied the matching of design tasks and knowledge resources, established a matching framework for cloud manufacturing patterns, and validated the quality of this method using product development process knowledge as an example. Liu et al [11] considered the resource matching problem between students and projects, classified them into different types based on their preferences, and developed a strategy proof mechanism to meet the requirements of fairness and efficiency. However, there are few existing studies on human job bilateral matching, and most of them are based on basic calculations, and the impact of matching results on individual matching satisfaction is rarely considered.…”

Section: Introductionmentioning

confidence: 99%

A Bilateral Matching Management Method for Intelligent Workgroups Considering the Balance of Personnel and Positions

Liu,

Lv,

Jiang

et al. 2024

Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December

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In order to solve the bilateral matching problem of digital person-post in the intelligent team, a bilateral matching model between personnel and positions considering the balance of overall and individual satisfaction has been proposed. Firstly, the preference order of employees and posts is calculated based on the principle of object element through the mutual evaluation between employees and posts. From the perspective of both enterprises and employees, considering the individual differences in satisfaction among employees. The optimization objective is to maximize the overall satisfaction and minimize the variance of individual satisfaction, the constraints are the maximum number of individual matches and the worst match limit. Following that, the NSGA-II algorithm is applied to solve the problem, and the chromosome is coded in two-dimensional 0-1. The Pareto front solution set of (0.24,0.28) is taken as the example of the shift management platform information of a company in the State Grid, and it is verified that the matching solution satisfying the overall and individual satisfaction balance can be obtained by the method of this paper. The matching model of this paper is implemented in the digital job matching function of the platform, which can provide the job manager with a matching solution that satisfies both sides.

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Mechanism Design for Mobility

Harada,

Itoh,

Matsubara

et al. 2024

Advanced Mathematical Science for Mobility Society

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This chapter presents the development of matching theory toward implementing the next-generation car-sharing systems, consisting of three topics: (1) online facility assignment problems on a line, (2) two-sided matching with flexible quotas: student-project-resource matching-allocation problem, and (3) formalizing station-based one-way car sharing as three-sided matching. The first two relate to developments in basic research, while the last one is application-oriented.

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Strategyproof Mechanism for Two-Sided Matching with Resource Allocation

Cited by 6 publications

References 58 publications

Strategyproof and fair matching mechanism for union of symmetric m-convex constraints

Strategyproof and fair matching mechanism for union of symmetric m-convex constraints

A Bilateral Matching Management Method for Intelligent Workgroups Considering the Balance of Personnel and Positions

Mechanism Design for Mobility

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