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 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.

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Publication Details

Journal
Biomimetics
Published
2024-10-18
DOI
https://doi.org/10.3390/biomimetics9100634
Citations
2
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.69
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article

A New Single-Parameter Bees Algorithm

Duc Truong Pham, Hamid Furkan Suluova
2 citations
Biomimetics
Metaheuristic Optimization Algorithms Research
0.69
article

A New Single-Parameter Bees Algorithm

Duc Truong Pham, Hamid Furkan Suluova
article en
2 citations

Abstract

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.

BiomimeticsVol. 9(10)
University of Birmingham (GB)
Sustainable cities and communities
Openalex Percentile: Top 24%
Metaheuristic Optimization Algorithms Research
0.69
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