—This paper presents an effective hybrid coevolutionary particle swarm optimization algorithm for solving constrained engineering design problems, which is based on simulated annealing (SA) , employing the notion of co-evolution to adapt penalty factors. By employing the SAbased selection for the best position of particles and swarms when updating the velocity in co-evolutionary particle swarm optimization algorithm. Simulation results based on well-known constrained engineering design problems demonstrate the effectiveness, efficiency and robustness on initial populations of the proposed, and can reach a high precision.
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