NDLI: Empirical testing on 3-Parents Differential Evolution (3PDE) for unconstrained function optimization

Content Provider	IEEE Xplore Digital Library
Author	Teng Nga Sing Teo, J. Hijazi, M.H.A.
Copyright Year	2007
Description	Author affiliation: Univ. Malaysia Sabah, Kota Kinabalu (Teng Nga Sing; Teo, J.; Hijazi, M.H.A.)
Abstract	The objective of this paper is to investigate whether the performance of the self-adaptive the parameters in 3PDE can improve the performance for function optimization. In this paper, we firstly propose three new algorithms (3PDE-SACr, 3PDE-SAF and 3PDE-SACrF). The preliminary testing is carried out to compare their performance with 3PDE to determine the best algorithm for the next step to self-adapt the population size. Here, the best algorithm from the preliminary testing will be chosen for the testing on self-adapting the population size in absolute and relative encodings. The preliminary testing showed that 3PDE-SAF performed the best for the first three proposed algorithms. So, 3PDE-SAF is chosen for the self-adaptive population size to test in absolute (3PDE-SAF-Abs) and relative (3PDE-SAF-Rel) encodings and the final result showed that 3PDE-SAF-Rel performed slightly better than all the proposed algorithms in terms of its average performance and its stability.
Starting Page	2259
Ending Page	2266
File Size	295874
Page Count	8
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4424752
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Testing Evolutionary computation
Content Type	Text
Resource Type	Article

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