The Runtime of Random Local Search on the Generalized Needle Problem
Neural and Evolutionary Computing
2025-10-14 v2 Artificial Intelligence
Data Structures and Algorithms
Abstract
In their recent work, C. Doerr and Krejca (Transactions on Evolutionary Computation, 2023) proved upper bounds on the expected runtime of the randomized local search heuristic on generalized Needle functions. Based on these upper bounds, they deduce in a not fully rigorous manner a drastic influence of the needle radius on the runtime. In this short article, we add the missing lower bound necessary to determine the influence of parameter on the runtime. To this aim, we derive an exact description of the expected runtime, which also significantly improves the upper bound given by C. Doerr and Krejca. We also describe asymptotic estimates of the expected runtime.
Cite
@article{arxiv.2403.08153,
title = {The Runtime of Random Local Search on the Generalized Needle Problem},
author = {Benjamin Doerr and Andrew James Kelley},
journal= {arXiv preprint arXiv:2403.08153},
year = {2025}
}
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18 pages