NDLI: On the analysis of a (1+1) adaptive memetic algorithm

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2011 IEEE Workshop on Memetic Computing (MC)

On the analysis of a (1+1) adaptive memetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Dinneen, M.J. Kuai Wei
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand (Dinneen, M.J.; Kuai Wei)
Abstract	A memetic algorithm is an evolutionary algorithm augmented with a local search. For many applications, researchers have applied variations of memetic algorithms and have gained very positive experimental results. But the theory of these variations of memetic algorithms is still underdeveloped. This paper defines the (1+1) adaptive memetic algorithm with a dynamic mutation probability, and analyzes two types of local searches. We then propose different classes of functions for studying the performance of evolutionary algorithms. We give time complexity analysis that proves our two local searches can outperform each other on different functions. Also we show that memetic algorithms with dynamic mutation probabilities can out-perform memetic algorithms with static mutation probabilities, and vice versa.
Starting Page	24
Ending Page	31
File Size	203859
Page Count	8
File Format	PDF
ISBN	9781467358910
DOI	10.1109/MC.2013.6608203
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-16
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Memetics Algorithm design and analysis Upper bound Heuristic algorithms Conferences Evolutionary computation Arrays
Content Type	Text
Resource Type	Article

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