Article

GSTF Journal on Computing (JoC)

, 3:36

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Load Allocation in Academic Environment: A Multi Objective PSO Approach

  • Sushri Samita RoutAffiliated withDepartment of Information Technology, Silicon Institute of Technology Email author 
  • , Bijan Bihari MisraAffiliated withDepartment of Information Technology, Silicon Institute of Technology
  • , Sasmita SamantaAffiliated withKIIT University

Abstract

In 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.

Keywords

Competency mapping Multi Objective Optimization Particle Swarm Optimization