Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems
In this study, the performance of Slime-Mould-Algorithm (SMA), a current Meta-Heuristic Search algorithm, is improved. In order to model the search process lifecycle process more effectively in the SMA algorithm, the solution candidates guiding the search process were determined using the fitness-di...
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Düzce University
2021-12-01
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| Series: | Düzce Üniversitesi Bilim ve Teknoloji Dergisi |
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| Online Access: | https://dergipark.org.tr/tr/download/article-file/2052433 |
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| author | Enes Cengiz Mehmet Fatih Işık Hamdi Kahraman Cemal Yılmaz Çağrı Suiçmez |
| author_facet | Enes Cengiz Mehmet Fatih Işık Hamdi Kahraman Cemal Yılmaz Çağrı Suiçmez |
| author_sort | Enes Cengiz |
| collection | DOAJ |
| description | In this study, the performance of Slime-Mould-Algorithm (SMA), a current Meta-Heuristic Search algorithm, is improved. In order to model the search process lifecycle process more effectively in the SMA algorithm, the solution candidates guiding the search process were determined using the fitness-distance balance (FDB) method. Although the performance of the SMA algorithm is accepted, it is seen that the performance of the FDB-SMA algorithm developed thanks to the applied FDB method is much better. CEC 2020, which has current benchmark problems, was used to test the performance of the developed FDB-SMA algorithm. 10 different unconstrained comparison problems taken from CEC 2020 are designed by arranging them in 30-50-100 dimensions. Experimental studies were carried out using the designed comparison problems and analyzed with Friedman and Wilcoxon statistical test methods. According to the results of the analysis, it has been seen that the FDB-SMA variations outperform the basic algorithm (SMA) in all experimental studies. |
| format | Article |
| id | doaj-art-f10c7670aafc4b1ca4e2c4fdc9983279 |
| institution | Kabale University |
| issn | 2148-2446 |
| language | English |
| publishDate | 2021-12-01 |
| publisher | Düzce University |
| record_format | Article |
| series | Düzce Üniversitesi Bilim ve Teknoloji Dergisi |
| spelling | doaj-art-f10c7670aafc4b1ca4e2c4fdc99832792025-08-20T03:53:52ZengDüzce UniversityDüzce Üniversitesi Bilim ve Teknoloji Dergisi2148-24462021-12-0196405410.29130/dubited.101620997Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization ProblemsEnes Cengiz0https://orcid.org/0000-0003-1127-2194Mehmet Fatih Işık1https://orcid.org/0000-0003-3064-7131Hamdi Kahraman2https://orcid.org/0000-0001-9985-6324Cemal Yılmaz3https://orcid.org/0000-0003-2053-052XÇağrı Suiçmez4https://orcid.org/0000-0002-9709-2276AFYON KOCATEPE UNIVERSITY, FACULTY OF TECHNOLOGYHITIT UNIVERSITY, FACULTY OF ENGINEERINGKARADENIZ TECHNICAL UNIVERSITY, OF FACULTY OF TECHNOLOGYMingachevirGAZI UNIVERSITY, FACULTY OF TECHNOLOGYIn this study, the performance of Slime-Mould-Algorithm (SMA), a current Meta-Heuristic Search algorithm, is improved. In order to model the search process lifecycle process more effectively in the SMA algorithm, the solution candidates guiding the search process were determined using the fitness-distance balance (FDB) method. Although the performance of the SMA algorithm is accepted, it is seen that the performance of the FDB-SMA algorithm developed thanks to the applied FDB method is much better. CEC 2020, which has current benchmark problems, was used to test the performance of the developed FDB-SMA algorithm. 10 different unconstrained comparison problems taken from CEC 2020 are designed by arranging them in 30-50-100 dimensions. Experimental studies were carried out using the designed comparison problems and analyzed with Friedman and Wilcoxon statistical test methods. According to the results of the analysis, it has been seen that the FDB-SMA variations outperform the basic algorithm (SMA) in all experimental studies.https://dergipark.org.tr/tr/download/article-file/2052433meta-sezgisel aramaslime mould algoritmasıuygunluk-mesafe dengesi (fdb)kıyaslama problemlerimeta-heuristic searchslime mould algorithmfitness-distance balance (fdb)benchmark problems |
| spellingShingle | Enes Cengiz Mehmet Fatih Işık Hamdi Kahraman Cemal Yılmaz Çağrı Suiçmez Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems Düzce Üniversitesi Bilim ve Teknoloji Dergisi meta-sezgisel arama slime mould algoritması uygunluk-mesafe dengesi (fdb) kıyaslama problemleri meta-heuristic search slime mould algorithm fitness-distance balance (fdb) benchmark problems |
| title | Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems |
| title_full | Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems |
| title_fullStr | Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems |
| title_full_unstemmed | Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems |
| title_short | Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems |
| title_sort | improved slime mould algorithm with fitness distance balance based guiding mechanism for global optimization problems |
| topic | meta-sezgisel arama slime mould algoritması uygunluk-mesafe dengesi (fdb) kıyaslama problemleri meta-heuristic search slime mould algorithm fitness-distance balance (fdb) benchmark problems |
| url | https://dergipark.org.tr/tr/download/article-file/2052433 |
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