A PSO Algorithm-Based Performance Evaluation Method for Enterprise-Level Transformation in the Power Industry

This paper proposes a work order-based performance evaluation model to address the common problems of assessment and “over-quantification” in the performance appraisal of front-line employees in electric power. The model quantifies the vertical counts of similar work items through multi-dimensional evaluation attributes, and clusters different work items horizontally using the subjective assessment weights of team leaders, aiming to fully explore the value information in the subjective assessment of the appraisers. In addition, this paper also proposes a dynamic stochastic topological particle swarm optimization (PSO) algorithm based on average degree for model solving. It provides an in-depth discussion on the particle coding method, constraints processing and strategy implementation in the algorithm. Finally, this paper verifies the validity of the model and algorithm by selecting five same types of workgroups for performance measurement, which provides a new method for the performance appraisal of front-line employees in electric power.