NEJul 12, 2013

Non-Elitist Genetic Algorithm as a Local Search Method

arXiv:1307.3463v46 citations
Originality Synthesis-oriented
AI Analysis

This provides theoretical guarantees for a non-elitist genetic algorithm's performance on optimization problems, though it is incremental as it builds on existing runtime analysis methods.

The paper tackled the problem of analyzing the runtime of a non-elitist genetic algorithm with tournament selection, showing that it can find a local optimum in polynomially bounded average time under certain conditions, specifically on problems with guaranteed local optima when parameters are appropriately set.

Sufficient conditions are found under which the iterated non-elitist genetic algorithm with tournament selection first visits a local optimum in polynomially bounded time on average. It is shown that these conditions are satisfied on a class of problems with guaranteed local optima (GLO) if appropriate parameters of the algorithm are chosen.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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