Benchmarking RCGAu on the Noiseless BBOB Testbed
Joint Authors
Sawyerr, Babatunde A.
Ali, M. Montaz
Adewumi, Aderemi Oluyinka
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-29
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
RCGAu is a hybrid real-coded genetic algorithm with “uniform random direction” search mechanism.
The uniform random direction search mechanism enhances the local search capability of RCGA.
In this paper, RCGAu was tested on the BBOB-2013 noiseless testbed using restarts till a maximum number of function evaluations (#FEs) of 105 × D are reached, where D is the dimension of the function search space.
RCGAu was able to solve several test functions in the low search dimensions of 2 and 3 to the desired accuracy of 108.
Although RCGAu found it difficult in getting a solution with the desired accuracy 108 for high conditioning and multimodal functions within the specified maximum #FEs, it was able to solve most of the test functions with dimensions up to 40 with lower precisions.
American Psychological Association (APA)
Sawyerr, Babatunde A.& Adewumi, Aderemi Oluyinka& Ali, M. Montaz. 2015. Benchmarking RCGAu on the Noiseless BBOB Testbed. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1079070
Modern Language Association (MLA)
Sawyerr, Babatunde A.…[et al.]. Benchmarking RCGAu on the Noiseless BBOB Testbed. The Scientific World Journal No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1079070
American Medical Association (AMA)
Sawyerr, Babatunde A.& Adewumi, Aderemi Oluyinka& Ali, M. Montaz. Benchmarking RCGAu on the Noiseless BBOB Testbed. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1079070
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1079070
