MPI-based parallel synchronous vector evaluated particle swarm optimization for multi-objective design optimization of composite structures

作者：Omkar S N^*; Venkatesh Akshay; Mudigere Mrunmaya

来源：Engineering Applications of Artificial Intelligence, 2012, 25(8): 1611-1627.

DOI：10.1016/j.engappai.2012.05.019

• Multi-objective optimization
• Vector evaluated particle swarm optimization (VEPSO)
• Message passing interface (MPI)
• Composite laminated plates
• Peer-to-peer communication
• Vector evaluated genetic algorithm (VEGA)

This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI%26apos;s collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem.

• 出版日期2012-12