Markov Chain Analyses of Random Local Search and Evolutionary Algorithm

DOI

10.2991/jrnal.2014.1.3.11How to use a DOI?

Keywords

Evolutionary algorithm, Random Local Search, Coupon collector's problem, Markov chain

Abstract

Theoretical studies of evolutionary algorithms (EAs) have been developed by researchers whose main interests are convergence properties of algorithms. In this paper, we report the computational complexity of an algorithm that is a variant of (1+1) EA, called Random Local Search (RLS). While a standard EA uses a mutation of flipping each bit in a parent string, RLS flips exactly one bit at each step. It has been noted the close resemblance of RLS with the coupon collector problem (CCP). CCP has a long history of probabilistic research, and many interesting results are obtained. This study makes use of such results with some modifications. We also show some useful results representing the evolution process of (1+1) EA.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Hiroshi Furutani
AU  - Hiroki Tagami
AU  - Makoto Sakamoto
AU  - Yifei Du
PY  - 2014
DA  - 2014/12/15
TI  - Markov Chain Analyses of Random Local Search and Evolutionary Algorithm
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 220
EP  - 224
VL  - 1
IS  - 3
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2014.1.3.11
DO  - 10.2991/jrnal.2014.1.3.11
ID  - Furutani2014
ER  -