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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Politeknik Negeri Padang
2017-11-01
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| Series: | JOIV: International Journal on Informatics Visualization |
| Subjects: | |
| Online Access: | http://joiv.org/index.php/joiv/article/view/65 |
| _version_ | 1831552068771381248 |
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| author | Kashif Hussain Mohd Najib Mohd Salleh Shi Cheng Rashid Naseem |
| author_facet | Kashif Hussain Mohd Najib Mohd Salleh Shi Cheng Rashid Naseem |
| author_sort | Kashif Hussain |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-17T03:20:15Z |
| format | Article |
| id | doaj.art-574f72cc93b64f9eb6f16b22dafe9adc |
| institution | Directory Open Access Journal |
| issn | 2549-9610 2549-9904 |
| language | English |
| last_indexed | 2024-12-17T03:20:15Z |
| publishDate | 2017-11-01 |
| publisher | Politeknik Negeri Padang |
| record_format | Article |
| series | JOIV: International Journal on Informatics Visualization |
| spelling | doaj.art-574f72cc93b64f9eb6f16b22dafe9adc2022-12-21T22:05:32ZengPoliteknik Negeri PadangJOIV: International Journal on Informatics Visualization2549-96102549-99042017-11-0114-221822310.30630/joiv.1.4-2.6538Common Benchmark Functions for Metaheuristic Evaluation: A ReviewKashif Hussain0Mohd Najib Mohd Salleh1Shi Cheng2Rashid Naseem3Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaUniversiti Tun Hussein Onn Malaysia, Johor, MalaysiaShaanxi Normal University, Xi’an, ChinaCity University of Science and Information Technology, Peshawar, PakistanIn 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.http://joiv.org/index.php/joiv/article/view/65benchmark test functionsnumerical optimizationmetaheuristic algorithmsoptimization. |
| spellingShingle | Kashif Hussain Mohd Najib Mohd Salleh Shi Cheng Rashid Naseem Common Benchmark Functions for Metaheuristic Evaluation: A Review JOIV: International Journal on Informatics Visualization benchmark test functions numerical optimization metaheuristic algorithms optimization. |
| 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 | benchmark test functions numerical optimization metaheuristic algorithms optimization. |
| url | http://joiv.org/index.php/joiv/article/view/65 |
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