Soft Computing

, Volume 23, Issue 9, pp 2995–3011 | Cite as

Multi-objective stable matching and distributional constraints

  • Mangesh GharoteEmail author
  • Nitin Phuke
  • Rahul Patil
  • Sachin Lodha


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.


Multi-objective Stable matching Goal programming Workforce allocation Heuristics Repair Distributional constraints 


Compliance with ethical standards

Conflict of interest

The authors have declared that no conflicts of interest exist.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Ethical approval

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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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Tata Consultancy Services, TCS Research TRDDCPuneIndia
  2. 2.SJM School of ManagementIIT BombayPowai, MumbaiIndia

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