Abstract
In this article, an efficient global hybrid optimization method is proposed combining central force optimization as a global optimizer and the Nelder-Mead algorithm as a local optimizer. After the final global iteration, a local optimization can be followed to further improve the solution obtained from central force optimization. The convergence capability of the hybrid central force optimization–Nelder-Mead approach is compared with other recent evolutionary-based algorithms using 13 benchmark functions grouped into unimodal and multimodal functions. In addition, the proposed algorithm is used to calculate accurately the resonant frequency and feed-point position of rectangular microstrip patch antenna elements with various dimensions and various substrate thicknesses. It is found that, in addition to decreasing the required evaluation number and the required processing time, excellent results are obtained.
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