An Improved Particle Swarm Optimisation Method for Performance Evaluation of Instructors

Abstract

Performance evaluation of counselors plays a vital role for education industry (schools, colleges, universities, and vocational colleges). The problem can be stated with the phrases; how to design reasonable and appropriate performance indicators? The objective of this research is to design an effective performance evaluation. The purpose of this study is to explore a new method of performance evaluation that combines strategic goals with personal development goals. The purpose of performance evaluation is to better motivate the enthusiasm of counselors. With the methodology, a new issue faced at modern colleges and universities is being resolved. Therefore, for explaining methodology, this study has carried out the application analysis of the fusion particle swarm algorithm (FPSA) in the performance evaluation of instructors. First, on the basis of comprehensive analysis of performance evaluation, it discusses the advantages and disadvantages of university performance evaluation. Secondly, particle swarm and fuzzy comprehensive evaluation methods are used in the research of instructor performance evaluation. Pass the superiority of this assessment system. Index parameter evaluation is from 2.5 to 3.0. The range indicates an excellent value. In result this improved particle swarm can be compared with the state of the art (Liu et al., 2019). In conclusive remarks, this study is to provide state-of-the-art study for the current research on the topic of instructor performance appraisal in colleges and universities.