Common benchmark functions for metaheuristic evaluation: a review

In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. Algorithms that perform well on a set of numerical optimization problems are considered as effective methods for solving real-world problems. Different researchers choose different set of f...

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Main Authors: Hussain, Kashif, Mohd Salleh, Mohd Najib, Shi, Cheng, Naseem, Rashid
Format: Article
Language:English
Published: JOIV 2017
Subjects:
Online Access:http://eprints.uthm.edu.my/4825/
http://eprints.uthm.edu.my/4825/1/AJ%202017%20%28665%29.pdf
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author Hussain, Kashif
Mohd Salleh, Mohd Najib
Shi, Cheng
Naseem, Rashid
author_facet Hussain, Kashif
Mohd Salleh, Mohd Najib
Shi, Cheng
Naseem, Rashid
author_sort Hussain, Kashif
building UTHM Institutional Repository
collection Online Access
description In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. Algorithms that perform well on a set of numerical optimization problems are considered as effective methods for solving real-world problems. Different researchers choose different set of functions with varying configurations, as there exists no standard or universally agreed test-bed. This makes hard for researchers to select functions that can truly gauge the robustness of a metaheuristic algorithm which is being proposed. This review paper is an attempt to provide researchers with commonly used experimental settings, including selection of test functions with different modalities, dimensions, the number of experimental runs, and evaluation criteria. Hence, the proposed list of functions, based on existing literature, can be handily employed as an effective test-bed for evaluating either a new or modified variant of any existing metaheuristic algorithm. For embedding more complexity in the problems, these functions can be shifted or rotated for enhanced robustness.
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spelling uthm-48252021-12-20T04:16:25Z http://eprints.uthm.edu.my/4825/ Common benchmark functions for metaheuristic evaluation: a review Hussain, Kashif Mohd Salleh, Mohd Najib Shi, Cheng Naseem, Rashid QA76 Computer software T Technology (General) In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. Algorithms that perform well on a set of numerical optimization problems are considered as effective methods for solving real-world problems. Different researchers choose different set of functions with varying configurations, as there exists no standard or universally agreed test-bed. This makes hard for researchers to select functions that can truly gauge the robustness of a metaheuristic algorithm which is being proposed. This review paper is an attempt to provide researchers with commonly used experimental settings, including selection of test functions with different modalities, dimensions, the number of experimental runs, and evaluation criteria. Hence, the proposed list of functions, based on existing literature, can be handily employed as an effective test-bed for evaluating either a new or modified variant of any existing metaheuristic algorithm. For embedding more complexity in the problems, these functions can be shifted or rotated for enhanced robustness. JOIV 2017 Article PeerReviewed text en http://eprints.uthm.edu.my/4825/1/AJ%202017%20%28665%29.pdf Hussain, Kashif and Mohd Salleh, Mohd Najib and Shi, Cheng and Naseem, Rashid (2017) Common benchmark functions for metaheuristic evaluation: a review. International Journal on Informatics Visualization, 1 (4-2). pp. 218-223. ISSN 2549-9610 https://dx.doi.org/10.30630/joiv.1.4-2.65
spellingShingle QA76 Computer software
T Technology (General)
Hussain, Kashif
Mohd Salleh, Mohd Najib
Shi, Cheng
Naseem, Rashid
Common benchmark functions for metaheuristic evaluation: a review
title Common benchmark functions for metaheuristic evaluation: a review
title_full Common benchmark functions for metaheuristic evaluation: a review
title_fullStr Common benchmark functions for metaheuristic evaluation: a review
title_full_unstemmed Common benchmark functions for metaheuristic evaluation: a review
title_short Common benchmark functions for metaheuristic evaluation: a review
title_sort common benchmark functions for metaheuristic evaluation: a review
topic QA76 Computer software
T Technology (General)
url http://eprints.uthm.edu.my/4825/
http://eprints.uthm.edu.my/4825/
http://eprints.uthm.edu.my/4825/1/AJ%202017%20%28665%29.pdf