Towards Academic Successor Selection Modelling with Genetic Algorithm in Multi-Criteria Problems

  • Authors

    • Atiqa Zukreena Zakuan
    • Shuzlina Abdul-Rahman
    • Hamidah Jantan
    • . .
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.23516
  • Genetic Algorithm, Multi-criteria, Successor planning, Talent management.

  • Abstract

    Succession planning is a subset of talent management that deals with multi-criteria and uncertainties which are quite complicated, ambiguous, fuzzy and troublesome. Besides that, the successor selection involves the process of searching the best candidate for a successor for an optimal selection decision. In an academic scenario, the quality of academic staff contributes to achieving goals and improving the performance of the university at the international level. The process of selecting appropriate academic staff requires good criteria in decision-making. The best candidate's position and criteria for the selection of academic staff is the responsibility of the Human Resource Management (HRM) to select the most suitable candidate for the required position. The various criteria that are involved in selecting academic staff includes research publication, teaching skills, personality, reputation and financial performance. Previously, most studies on multi-criteria decision-making adopt Fuzzy Analytical Hierarchy Process (FAHP). However, this method is more complex because it involved many steps and formula and may not produce the optimum results. Therefore, Genetic Algorithm (GA) is proposed in this research to address this problem in which a fitness function for the successor selection is based on the highest fitness value of each chromosome.

     


     


     

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  • How to Cite

    Zukreena Zakuan, A., Abdul-Rahman, S., Jantan, H., & ., . (2018). Towards Academic Successor Selection Modelling with Genetic Algorithm in Multi-Criteria Problems. International Journal of Engineering & Technology, 7(4.33), 130-133. https://doi.org/10.14419/ijet.v7i4.33.23516

    Received date: 2018-12-09

    Accepted date: 2018-12-09

    Published date: 2018-12-09