Local Search with Progress Spectrum Adaptation

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The paper examines the efficiency of search algorithms that utilize intergenerational information for optimization, highlighting the adaptation of process parameters. It addresses the high costs associated with traditional strategies and introduces an elegant algorithm that transfers adaptation processes into the spectral range of object variables. The focus is on the convergence behavior when processing simple yet high-dimensional quality functions, providing insights into improving optimization strategies in biological contexts.