An improved dynamic membrane evolutionary algorithm for constrained engineering design problems.

Constrained global optimization is a highly important and challenging task in the field of optimization, and is embedded in many science and engineering optimizations. In this paper, an improved dynamic membrane evolutionary algorithm based on particle swarm optimization and differential evolution (IDMEA-PSO/DE) is proposed to solve constrained engineering design problems. The method combines the dynamic membrane structure of P systems and the PSO/DE search strategy. The performance of IDMEA-PSO/DE is tested on several well-known engineering design problems. The results of the simulation experiments show that the proposed algorithm is effective and outperforms other state-of-the-art-algorithms. [ABSTRACT FROM AUTHOR]