A Particle Swarm Optimization Algorithm With Novel Expected Fitness Evaluation for Robust Optimization Problems

In this paper, an improved particle swarm optimization (PSO) algorithm for robust optimization problems is proposed. The new algorithm, named robust particle swarm optimization (RPSO), deeps basic concepts of the PSO, results in dynamic determination of the robust optimal solution by using a 2n-quadrant-longest-distance expected fitness evaluation strategy in n-D space, and obtains robustness against the perturbation of design variables. The efficiency and advantages of the proposed algorithm are verified by the application to a mathematical function and a practical electromagnetic problem.

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