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Resolving the Recruitment and Selection Problem as NP-Hard Problem


  • Centre for Information Technology and Systems, University of Lagos, Lagos, Nigeria
  • Department of Computer Science, Covenant University, Ota, Nigeria


Background/Objectives: As organizations increasingly strive to attract and retain high calibre ICT-compliant staff, recruitment and selection is attracting huge attention. This paper classified the recruitment and selection problem as NP-hard problem and applied metaheuristic algorithm to solve it. Methods/Statistical Analysis: This study focused on University of Lagos, Nigeria as case study and applied computational theory in the form of metaheuristic algorithm in a bid to improve on the existing recruitment and selection process. We reviewed literature, gathered requirements, designed a system and statically tested the process-correctness of the proposed system. The operational recruitment and selection data collected and used for statical testing were obtained from secondary materials of the University. Findings: We were able to establish that the recruitment and selection problem in University of Lagos, Nigeria is NP-Hard and equally confirmed appropriateness of applying metaheuristic solution rather than exact algorithm to such problem, given its complex and varied nature. In our view, this is an addition to the growing body of knowledge of the metaheuristic community. Also, the research outcome is an addition to the human resource management community knowledge space. Against the backdrop that human resources are germane to the socio-economic transformation of nations coupled with the challenges of obtaining optimal solutions (best-known candidates) from a teeming pool of applicants, human resource experts are excited that a value-addition metaheuristic solution such as ours can reduce their recruitment and selection stress by about 50%. With the right crop of employees, set organizational goals and objectives can be achieved in the most efficient and effective fashion. Applications/Improvements: The study outcome is a software architecture that will scaleup the search for optimal solutions (best candidates) from any pool of job applicants in a timely and cost-effective fashion. This best-fit search apparatus will help human resource experts in aligning organization’s human resource strategy with its corporate strategy and objectives.


NP-Hard, Problem, Recruitment, Resolving, Selection.

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