WOSCA: A Hybrid Algorithm of Whale Optimization Algorithm and Sine Cosine Algorithm for Large-scale Optimization Problems

• DOI: 10.1145/3650400.3650573
• Publication Date: 2024-04-17T12:33:18Z
• Authors: Shan Zhang; Linru Ma; Yingchao Wang
• Keywords: Premature convergence; Local optimum; Optimization algorithm; Robustness; Benchmark (surveying)

The whale optimization algorithm (WOA) and sine cosine (SCA) exhibit limitations, such as premature convergence local optima, for solving large-scale problems. To address this problem, a novel hybrid called WOSCA is proposed. leverages orthogonal Latin squares to obtain the initial population with balanced dispersion neat comparability, integrates search mechanism of SCA into WOA enhance balance algorithm's exploration exploitation. Moreover, avoid falling optimum diversity population, dynamic inertia weight strategy introduced an exhaustive nearby space. Twenty high-dimensional benchmark functions are selected evaluate effectiveness proposed method. results demonstrate that has better accuracy stronger robustness when