A New Single-Parameter Bees Algorithm
Based on bee foraging behaviour, the Bees Algorithm (BA) is an optimisation metaheuristic algorithm which has found many applications in both the continuous and combinatorial domains. The original version of the Bees Algorithm has six user-selected parameters: the number of scout bees, the number of...
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MDPI AG
2024-10-01
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| author | Hamid Furkan Suluova Duc Truong Pham |
| author_facet | Hamid Furkan Suluova Duc Truong Pham |
| author_sort | Hamid Furkan Suluova |
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| description | Based on bee foraging behaviour, the Bees Algorithm (BA) is an optimisation metaheuristic algorithm which has found many applications in both the continuous and combinatorial domains. The original version of the Bees Algorithm has six user-selected parameters: the number of scout bees, the number of high-performing bees, the number of top-performing or “elite” bees, the number of forager bees following the elite bees, the number of forager bees recruited by the other high-performing bees, and the neighbourhood size. These parameters must be chosen with due care, as their values can impact the algorithm’s performance, particularly when the problem is complex. However, determining the optimum values for those parameters can be time-consuming for users who are not familiar with the algorithm. This paper presents BA<sub>1</sub>, a Bees Algorithm with just one parameter. BA<sub>1</sub> eliminates the need to specify the numbers of high-performing and elite bees and other associated parameters. Instead, it uses incremental k-means clustering to divide the scout bees into groups. By reducing the required number of parameters, BA<sub>1</sub> simplifies the tuning process and increases efficiency. BA<sub>1</sub> has been evaluated on 23 benchmark functions in the continuous domain, followed by 12 problems from the TSPLIB in the combinatorial domain. The results show good performance against popular nature-inspired optimisation algorithms on the problems tested. |
| format | Article |
| id | doaj-art-4acde50c2531492ab9c4cf12f95d3dd6 |
| institution | OA Journals |
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| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
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| series | Biomimetics |
| spelling | doaj-art-4acde50c2531492ab9c4cf12f95d3dd62025-08-20T02:11:14ZengMDPI AGBiomimetics2313-76732024-10-0191063410.3390/biomimetics9100634A New Single-Parameter Bees AlgorithmHamid Furkan Suluova0Duc Truong Pham1Department of Mechanical Engineering, The University of Birmingham, Birmingham B15 2TT, UKDepartment of Mechanical Engineering, The University of Birmingham, Birmingham B15 2TT, UKBased on bee foraging behaviour, the Bees Algorithm (BA) is an optimisation metaheuristic algorithm which has found many applications in both the continuous and combinatorial domains. The original version of the Bees Algorithm has six user-selected parameters: the number of scout bees, the number of high-performing bees, the number of top-performing or “elite” bees, the number of forager bees following the elite bees, the number of forager bees recruited by the other high-performing bees, and the neighbourhood size. These parameters must be chosen with due care, as their values can impact the algorithm’s performance, particularly when the problem is complex. However, determining the optimum values for those parameters can be time-consuming for users who are not familiar with the algorithm. This paper presents BA<sub>1</sub>, a Bees Algorithm with just one parameter. BA<sub>1</sub> eliminates the need to specify the numbers of high-performing and elite bees and other associated parameters. Instead, it uses incremental k-means clustering to divide the scout bees into groups. By reducing the required number of parameters, BA<sub>1</sub> simplifies the tuning process and increases efficiency. BA<sub>1</sub> has been evaluated on 23 benchmark functions in the continuous domain, followed by 12 problems from the TSPLIB in the combinatorial domain. The results show good performance against popular nature-inspired optimisation algorithms on the problems tested.https://www.mdpi.com/2313-7673/9/10/634Bees Algorithmnature-inspired algorithmbee-inspired algorithmmetaheuristicscontinuous optimisationcombinatorial optimisation |
| spellingShingle | Hamid Furkan Suluova Duc Truong Pham A New Single-Parameter Bees Algorithm Biomimetics Bees Algorithm nature-inspired algorithm bee-inspired algorithm metaheuristics continuous optimisation combinatorial optimisation |
| title | A New Single-Parameter Bees Algorithm |
| title_full | A New Single-Parameter Bees Algorithm |
| title_fullStr | A New Single-Parameter Bees Algorithm |
| title_full_unstemmed | A New Single-Parameter Bees Algorithm |
| title_short | A New Single-Parameter Bees Algorithm |
| title_sort | new single parameter bees algorithm |
| topic | Bees Algorithm nature-inspired algorithm bee-inspired algorithm metaheuristics continuous optimisation combinatorial optimisation |
| url | https://www.mdpi.com/2313-7673/9/10/634 |
| work_keys_str_mv | AT hamidfurkansuluova anewsingleparameterbeesalgorithm AT ductruongpham anewsingleparameterbeesalgorithm AT hamidfurkansuluova newsingleparameterbeesalgorithm AT ductruongpham newsingleparameterbeesalgorithm |