Benchmarking RCGAu on the Noiseless BBOB Testbed

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 func...

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Main Authors: Babatunde A. Sawyerr, Aderemi O. Adewumi, M. Montaz Ali
Format: Article
Language:English
Published: Wiley 2015-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2015/734957
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author Babatunde A. Sawyerr
Aderemi O. Adewumi
M. Montaz Ali
author_facet Babatunde A. Sawyerr
Aderemi O. Adewumi
M. Montaz Ali
author_sort Babatunde A. Sawyerr
collection DOAJ
description 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.
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publisher Wiley
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series The Scientific World Journal
spelling doaj-art-c50fafe93f90412e9bdd06f8c7c0876e2025-08-20T02:18:46ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/734957734957Benchmarking RCGAu on the Noiseless BBOB TestbedBabatunde A. Sawyerr0Aderemi O. Adewumi1M. Montaz Ali2School of Mathematics, Statistics and Computer Science, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Westville, South AfricaSchool of Mathematics, Statistics and Computer Science, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Westville, South AfricaSchool of Computational and Applied Mathematics, Faculty of Science and TCSE, Faculty of Engineering and Built Environment, University of the Witwatersrand, Johannesburg, South AfricaRCGAu 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.http://dx.doi.org/10.1155/2015/734957
spellingShingle Babatunde A. Sawyerr
Aderemi O. Adewumi
M. Montaz Ali
Benchmarking RCGAu on the Noiseless BBOB Testbed
The Scientific World Journal
title Benchmarking RCGAu on the Noiseless BBOB Testbed
title_full Benchmarking RCGAu on the Noiseless BBOB Testbed
title_fullStr Benchmarking RCGAu on the Noiseless BBOB Testbed
title_full_unstemmed Benchmarking RCGAu on the Noiseless BBOB Testbed
title_short Benchmarking RCGAu on the Noiseless BBOB Testbed
title_sort benchmarking rcgau on the noiseless bbob testbed
url http://dx.doi.org/10.1155/2015/734957
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