Comparison between Particle Swarm Optimization,Differential Evolution and Multi-parents Crossover

摘要

Particle swarm optimization (PSO),differential evolution (DE) and multi-parents crossover (MPC) are the evolutionary computation paradigms,all of which have shown superior performance on complex non-linear function optimization problems.This paper detects the underlying relationship between them and then qualitatively proves that these heuristic approaches from different theoretical principles are consistent in form.Comparison experiments involving eight test functions well studied in the evolutionary optimization literature are used to highlight some performance differences between the techniques.The results from our study show that DE generally outperforms the other algorithms.