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Whale Optimization Algorithm Guided by Complex Networks
Abstract
The Whale Optimization Algorithm is a brand new bio inspired optimization algorithm. In this work, we propose an alternative using an underlying small-world complex network to guide the whales in the matching selection with other whales in the updating process to find the best possible solution in each iteration instead of a random selection. We perform a comparison between the original Whale Optimization Algorithm with the proposed model in some optimization functions tested. The obtained results are auspicious in terms of fitness convergence. Optimization algorithm guiding small-world complex networks show favorable results, as suggested by previous research.
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