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Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem

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Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem

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dc.contributor.author Rabiei, Peyman es_ES
dc.contributor.author Arias-Aranda, Daniel es_ES
dc.date.accessioned 2021-06-03T09:16:13Z
dc.date.available 2021-06-03T09:16:13Z
dc.date.issued 2021-06-02
dc.identifier.uri http://hdl.handle.net/10251/167258
dc.description.abstract [EN] In today’s competitive markets, the role of human resources as a sustainable competitive advantage is undeniable. Reliable hiring decisions for personnel assignation contribute greatly to a firms’ success. The Personnel Assignment Problem (PAP) relies on assigning the right people to the right positions. The solution to the PAP provided in this paper includes the introducing and testing of an algorithm based on a combination of a Fuzzy Inference System (FIS) and a Genetic Algorithm (GA). The evaluation of candidates is based on subjective knowledge and is influenced by uncertainty. A FIS is applied to model experts’ qualitative knowledge and reasoning. Also, a GA is applied for assigning assessed candidates to job vacancies based on their competency and the significance of each position. The proposed algorithm is applied in an Iranian company in the chocolate industry. Thirty-five candidates were evaluated and assigned to three different positions. The results were assessed by ten staff managers and the algorithm results proved to be satisfactory in discovering desirable solutions. Also, two GA selection techniques (tournament selection and proportional roulette wheel selection) were used and compared. Results show that tournament selection has better performance than proportional roulette wheel selection. es_ES
dc.description.sponsorship This research has been developed under funds of the H2020-MSCA-RISE-2018 project 823759 REMESH Research Network on Emergency Resources Supply Chain. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof WPOM-Working Papers on Operations Management es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Fuzzy Inference Systems es_ES
dc.subject Genetic Algorithm es_ES
dc.subject Personnel Assignment Problem es_ES
dc.subject Disasters Management and Emergencies es_ES
dc.subject Cost-benefit ratio es_ES
dc.title Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/wpom.14699
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/823759/EU/Research Network on Emergency Resources Supply Chain/
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Rabiei, P.; Arias-Aranda, D. (2021). Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem. WPOM-Working Papers on Operations Management. 12(1):1-27. https://doi.org/10.4995/wpom.14699 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/wpom.14699 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 27 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 1989-9068
dc.relation.pasarela OJS\14699 es_ES
dc.contributor.funder European Commission es_ES
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