Abstract
AbstractIn an Organization, mapping the competency of personnel with different level of expertise, skill set, and experience in professional fields is a tough, complex but essential task. In this work, we have considered an Engineering College with moderate number of faculties with different level of experience, expertise and research exposure. Here we have considered the load assignment to the faculties at the beginning of a semester as the competency mapping task. Each faculty having capabilities of teaching different subjects out of the total set of papers needs to take about two theory papers with or without laboratory component. The decisive factors for subject assignment may be depth of knowledge, sincerity, class management, contribution towards research, text book publication. Further preference of the faculty member should be considered with top priority unless there are some valid constraints. Again the teaching personnel in a department hold different designations and different administrative responsibility, therefore each of them cannot be assigned equal hours of teaching load. The All India Council for Technical Education (AICTE) guidelines is considered as a baseline for assignment of teaching load. The decisive factors are considered as objectives to be optimized and multi-objective particle Swarm optimization (MOPSO) is employed to perform the competency mapping task. The simulation results show the effectiveness of this approach.
Highlights
There has been lot of attempts of late to find the real reason behind the deteriorating employability aspect of the T-school (Technical School) graduates
Each faculty differs from the other in terms of experience, qualification, expertise, skills and his own expectations from his job. It becomes very difficult on the part of the Heads of the Departments to always find the best fit between the requirement and the expectations of the faculty in terms of subjects assigned to him as the teaching load
In the third section we introduce the concept of Multi-objective optimization followed by Particle Swarm Optimization (PSO) and multi-objective Optimization (MOPSO) respectively in the fourth and fifth sections, along with their applications
Summary
There has been lot of attempts of late to find the real reason behind the deteriorating employability aspect of the T-school (Technical School) graduates. Each faculty differs from the other in terms of experience, qualification, expertise, skills and his own expectations from his job. It becomes very difficult on the part of the Heads of the Departments to always find the best fit between the requirement (allotting subject in this context) and the expectations of the faculty in terms of subjects assigned to him as the teaching load. In this paper we have suggested a method to allocate subjects to faculties taking into account their preferences, experience, knowledge, skills and the requirements of the department. In the sixth section we present the problem formulation taking the Computer Science Department at our Institute into account including the manual process of load allocation.
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