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Academic Staff planning, allocation and optimization using Genetic Algorithm under the framework of Fuzzy Goal Programming

机译:在模糊目标规划框架下使用遗传算法的学术人员规划,分配和优化

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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.
机译:高等教育是在兴趣的兴趣中心,基于结果的教育(OBE)学习以教育为中心的环境,因为寻求更好的人类生活和生活以及技术方面的进一步改善。主要挑战仍在为资源人员提供最佳的知识转移,以应对职业机会继续进行职业发展方案的优质知识转移。因此,开放新的学术部门来解决社会需求是一个经常的过程,与现有部门的资源增强平行,与越来越多的学生保持平衡。在这一问题中,由于自己的利益,辞职和资源保留了内在的不确定性。这就是为什么大多数教学组织遇到学术部门教学人员资源配置困难的原因。这一拟议工作的目的是展示遗传算法(GA)如何应用于目标编程(GP)的大学资源规划问题,以加强大学学术标准的学术标准规划过程中的术语。在模型制定中,教授,助理教授,助理教授,访问/兼职教师和非教学人员以及每个学术部门的预算目标的人数被确定和描述。在解决方案过程中,概念遗嘱借助大学管理系统的分数目标和目标间隔的学术资源规划问题的目标规划(GP)。

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