Upper Bounds on the Running Time of the Univariate Marginal Distribution Algorithm on OneMax

The Univariate Marginal Distribution Algorithm (UMDA) is a randomized search heuristic that builds a stochastic model of the underlying optimization problem by repeatedly sampling λ solutions and adjusting the model according to the best μ samples. We present a running time analysis of the UMDA on t...

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Bibliographic Details
Published in:	Algorithmica Vol. 81; no. 2; pp. 632 - 667
Main Author:	Witt, Carsten
Format:	Journal Article
Language:	English
Published:	New York Springer US 15.02.2019 Springer Nature B.V
Subjects:	Algorithm Analysis and Problem Complexity Algorithms Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Lower bounds Mathematics of Computing Run time (computers) Special Issue on Theory of Genetic and Evolutionary Computation Theory of Computation Upper bounds New York Randomized search heuristics UMDA Estimation-of-distribution algorithms Running time analysis
ISSN:	0178-4617, 1432-0541
Online Access:	Get full text
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