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- W3036396914 abstract "Abstract Higher Education is in the centre of interest in this era of Outcome Based Education (OBE) in learning centric environment due to in quest of better human life and living and further improvement in technological aspects. The main challenges remain in providing resource persons in quest of optimum knowledge transfer to address quality concern right from career opportunities to continuing education programs. So opening up new academic departments to address the societal needs is a regular process in parallel to resource enhancement in the existing departments, keeping balance with the increasing number of students. In this problem, there are inherent uncertainties in terms of resignation and retention of the resource persons due to their own interest. That’s the reason why most of the teaching organizations encounter the difficulties of resource allocation of teaching personnel in the academic departments. The objective of this proposed work is to demonstrate how the Genetic Algorithm (GA) is applied in goal programming (GP) formulation of the problem for university resource planning of academic personnel to different departments for enhancement of academic standards of a university on a long-term basis in the planning process. In model formulation, the number of Professor, Associate Professor, Assistant Professor, Visiting/Part-Time faculty member and Non-teaching staff along with the budget goals of each of the academic departments are identified and described. In the solution process, the ideais to employ GA to the goal programming (GP) construction of academic resource planning problems with fractional goals and target intervals in university management system." @default.
- W3036396914 created "2020-06-25" @default.
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- W3036396914 date "2020-01-01" @default.
- W3036396914 modified "2023-10-02" @default.
- W3036396914 title "Academic Staff planning, allocation and optimization using Genetic Algorithm under the framework of Fuzzy Goal Programming" @default.
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- W3036396914 doi "https://doi.org/10.1016/j.procs.2020.05.130" @default.
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