Abstract
Due to the extensions of businesses, companies have multi-positions to be filled every year. On the other hand, many experienced as well as fresh applicants are looking for new experiences that challenge their abilities, stimulate their knowledge, and increase their income. In a very robust competitive environment, leading organizations are looking for appropriate qualified people to cover the open positions that result from the business extension or from vacancies due to resignations and lack of capabilities.
The usual practice of originations is to hold nominee applications with the recruiting unit. Thus, the objective of the research is to provide the Human Resources Department with a valid systematic methodology to ensure that highly qualified employees are selected as soon as a department needs them, and then to guarantee the appropriateness of the final selection in terms of multi-qualifications criteria.
We develop a mathematical model to help the HR department of a local bank select candidates classified into three categories, experts, fresh graduates, and processors, based on the following criteria:
For experts, the model considers specialty, languages, interview feedback, residency, age, years of experience, and required packages.
Concerning graduates and processors, we consider major, languages, interview feedback, residency, age, bank’s IQ test, and GPA.
The model, an integer program, is built to satisfy the following requirements:
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The minimum number of required employees, the field of experience, and the major
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Language constraints
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Interview score requirements
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Residency requirements
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IQ test related to the whole applicants
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Number of years of experience score
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Required package as opposed to other applicants
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GPA score
The minimization of the objective function consists of selecting the least number of candidates who satisfy all the constraints above.
The model is a very fast tool for helping the Bank to use rationally the existing resources and making the best decision in terms of selection of the most adequate candidates.
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Bouras, A. (2018). Optimal Selection of Superlative Candidates for Open Positions Using Linear Programming. In: Tadj, L., Garg, A. (eds) Emerging Challenges in Business, Optimization, Technology, and Industry. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-58589-5_9
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DOI: https://doi.org/10.1007/978-3-319-58589-5_9
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-58588-8
Online ISBN: 978-3-319-58589-5
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