Abstract
The Whale optimization Algorithm (WOA) is a recently introduced metaheuristic that has shown a promising performance in solving optimization problems. To further improve the search performance of WOA, the Chaotic Local Search (CLS) mechanism is incorporated into WOA. Ten different chaotic maps are investigated to give insights into the influence of CLS in the WOA. The goal is to compare the performance of the Whale optimization Algorithm with Chaotic Local Search (WOACLS) with the standard WOA and the Chaotic WOA (CWOA) by applying them to twenty well-known benchmark functions. Results show that the performance of WOACLS depends on both, the characteristics of the embedded chaotic map and the properties of the search landscape of the optimization problems considered.
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