A multi-stage particle swarm for optimum design of truss structures

作者：Talatahari S^*; Kheirollahi M; Farahmandpour C; Gandomi A H

来源：Neural Computing & Applications, 2013, 23(5): 1297-1309.

DOI：10.1007/s00521-012-1072-5

• Optimum design
• Particle swarm optimization
• Truss structures

The contribution of this study is to propose a multi-stage particle swarm optimization (MSPSO) for structural optimization. In this paper, three auxiliary improving mechanisms are added to the standard particle swarm optimization (PSO) in order to enhance its efficiency and reliability dealing with optimum design of truss structures. These mechanisms effectively accelerate the convergence rate of the PSO and also make it robust to attain better optimum solutions during various runs of the algorithm. The effectiveness of the MSPSO is illustrated by several benchmark structural optimization problems. Results demonstrate the efficiency and robustness of the proposed MSPSO algorithm compared to the standard version of the PSO.

• 出版日期2013-10