Multi-objective stable matching and distributional constraints
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In this paper, we study a centralized matching scheme that has to assign a set of agents to a set of jobs by meeting distributional constraints. The scheme has to maximize social welfare and fairness offered by the matching to the parties. Furthermore, the allocation needs to minimize the number of blocking pairs. The problem is NP-hard and hence computationally challenging. Nonetheless, the users expect good solutions that can be generated quickly. We propose linear programming-based improvement heuristics to solve this multi-criteria stable matching problem. Our approach finds an equitable and global welfare stable matching solution in significantly lesser time. We then demonstrate the applicability of our proposed model and the solution methodology in a workforce allocation problem faced by software projects.
KeywordsMulti-objective Stable matching Goal programming Workforce allocation Heuristics Repair Distributional constraints
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Conflict of interest
The authors have declared that no conflicts of interest exist.
Informed consent was obtained from all individual participants included in the study.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
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