Differential Evolution with Nearest & Better Option for Function Optimization
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Differential evolution is the conventional algorithm with the fastest convergence speed, but it may be trapped local optimal solution easily, so many researchers devote themselves into improve DE. Whale swarm algorithm (WSA) is a new algorithm with niching strategy we proposed previously, it is featured with simple mutation strategy and powerful global search capability, but for functions with high dimensions, it converges slower than conventional algorithms. Based on this fact, we proposed a new DE algorithm, called DE with nearest & better option (NbDE). In order to evaluate the performance of NbDE, we compare NbDE with several meta-heuristic algorithms in nine classical benchmark functions with different dimensions. The result have shown that NbDE outperforms other algorithms in convergence speed and accuracy.
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