A branch-and-bound algorithm for team formation on social networks

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buir.contributor.authorBerktaş, Nihal
buir.contributor.orcidBerktaş, Nihal|0000-0002-3510-0808
dc.citation.epage1176en_US
dc.citation.issueNumber3en_US
dc.citation.spage1162en_US
dc.citation.volumeNumber33en_US
dc.contributor.authorBerktaş, Nihal
dc.contributor.authorYaman, Hande
dc.date.accessioned2022-02-14T13:07:57Z
dc.date.available2022-02-14T13:07:57Z
dc.date.issued2021
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractThe team formation problem (TFP) aims to construct a capable team that can communicate and collaborate effectively. The cost of communication is quantified using the proximity of the potential members in a social network. We study a TFP with two measures for communication effectiveness; namely, we minimize the sum of communication costs, and we impose an upper bound on the largest communication cost. This problem can be formulated as a constrained quadratic set covering problem. Our experiments show that a general purpose solver is capable of solving small and medium-sized instances to optimality. We propose a branch-and-bound algorithm to solve larger sizes: we reformulate the problem and relax it in such a way that it decomposes into a series of linear set covering problems, and we impose the relaxed constraints through branching. Our computational experiments show that the algorithm is capable of solving large-size instances, which are intractable for the solver. Summary of Contribution: This paper presents an exact algorithm for the Team Formation Problem (TFP), in which the aim is, given a project and its required skills, to construct a capable team that can communicate and collaborate effectively. This combinatorial opti mization problem is modeled as a quadratic set covering problem. The study provides a novel branch-and-bound algorithm where a reformulation of the problem is relaxed so that it decomposes into a series of linear set covering problems and the relaxed constraints are imposed through branching. The algorithm is able to solve instances that are intractable for commercial solvers. The study illustrates an efficient usage of algorithmic methods and modelling techniques for an operations research problem. It contributes to the field of computational optimization by proposing a new application as well as a new algorithm to solve a quadratic version of a classical combinatorial optimization problem.en_US
dc.identifier.doi10.1287/ijoc.2020.1000en_US
dc.identifier.eissn1526-5528
dc.identifier.issn1091-9856
dc.identifier.urihttp://hdl.handle.net/11693/77332
dc.language.isoEnglishen_US
dc.publisherInstitute for Operations Research and the Management Sciences (INFORMS)en_US
dc.relation.isversionofhttps://doi.org/10.1287/ijoc.2020.1000en_US
dc.source.titleINFORMS Journal on Computingen_US
dc.subjectTeam formation problemen_US
dc.subjectQuadratic set coveringen_US
dc.subjectBranch and bounden_US
dc.subjectReformulationen_US
dc.titleA branch-and-bound algorithm for team formation on social networksen_US
dc.typeArticleen_US

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