A hybrid cuckoo search algorithm with feasibility-based rule for constrained structural optimization

Constrained optimization problems are very important as they are encountered in many science and engineering applications. As a novel evolutionary computation technique, cuckoo search (CS) algorithm has attracted much attention and wide applications, owing to its easy implementation and quick convergence. A hybrid cuckoo pattern search algorithm (HCPS) with feasibility-based rule is proposed for solving constrained numerical and engineering design optimization problems. This algorithm can combine the stochastic exploration of the cuckoo search algorithm and the exploitation capability of the pattern search method. Simulation and comparisons based on several well-known benchmark test functions and structural design optimization problems demonstrate the effectiveness, efficiency and robustness of the proposed HCPS algorithm.

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