摘要

This paper presents an approach in which grey relational analysis with entropy weight is incorporated into particle swarm optimization algorithm (PSO) in order to allow this heuristic to handle multi-objective optimization (MO). In our algorithm, grey relational analysis is used to guide particles flight for MOPSO, and entropy weight is also incorporated into grey relational analysis in order to enrich the exploratory capabilities and realize the intelligence evaluation. The proposed approach is validated by using several test functions and practical optimal example. Results indicate that the improved algorithm is effective, has the characteristics of easy realization, fast convergence speed, and can be considered a viable alternative to solve MO problems.