Running Time Analysis of the (1+1)-EA for OneMax and LeadingOnes Under Bit-Wise Noise

In many real-world optimization problems, the objective function evaluation is subject to noise, and we cannot obtain the exact objective value. Evolutionary algorithms (EAs), a type of general-purpose randomized optimization algorithm, have been shown to be able to solve noisy optimization problems...

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Bibliographic Details
Published in:	Algorithmica Vol. 81; no. 2; pp. 749 - 795
Main Authors:	Qian, Chao, Bian, Chao, Jiang, Wu, Tang, Ke
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 Evolutionary algorithms Low noise Mathematics of Computing Noise levels Optimization Polynomials Run time (computers) Sampling Special Issue on Theory of Genetic and Evolutionary Computation Theory of Computation Noisy optimization Evolutionary algorithms Sampling Computational complexity Running time analysis
ISSN:	0178-4617, 1432-0541
Online Access:	Get full text
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