Multi-Swarm Bees Algorithm with GPU Computing for Belt Conveyor Production System

Abstract The paper presents the application of the Bees Algorithm to solve the NP - hard optimisation problem related to the Belt Conveyor Systems. For this purpose, the mathematical model for a real-life example of the Belt Conveyor Production System (BCPS) was defined. Creating the multi-swarm Bees Algorithm for solving this optimisation problem on a CUDA platform within the accepted time for real production systems, and analyzing the impact of control parameters on the algorithm's performance are the main objectives of our study. Moreover, the impact of the different block and grid sizes was checked. To ensure comparability of the results, extensive tests have been carried out using the multi-swarm version designed for the GPU and the mono-swarm version designed for the CPU platform. The results show that the proposed multi-swarm Bees Algorithm algorithm for the CUDA platform gives considerable acceleration of the calculations, but often requires the larger size of the neighbourhood.

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Publication Details

Journal
Journal of Artificial Intelligence and Soft Computing Research
Published
2026-07-01
DOI
https://doi.org/10.2478/jaiscr-2026-0023
Primary Topic
Belt Conveyor Systems Engineering
Type
article
Field-Weighted Citation Impact
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article

Multi-Swarm Bees Algorithm with GPU Computing for Belt Conveyor Production System

Wojciech Chmiel, Joanna Kwiecień, Paweł Kolendo
Journal of Artificial Intelligence and Soft Computing Research
Belt Conveyor Systems Engineering
article

Multi-Swarm Bees Algorithm with GPU Computing for Belt Conveyor Production System

Wojciech Chmiel, Joanna Kwiecień, Paweł Kolendo
article en

Abstract

Abstract The paper presents the application of the Bees Algorithm to solve the NP - hard optimisation problem related to the Belt Conveyor Systems. For this purpose, the mathematical model for a real-life example of the Belt Conveyor Production System (BCPS) was defined. Creating the multi-swarm Bees Algorithm for solving this optimisation problem on a CUDA platform within the accepted time for real production systems, and analyzing the impact of control parameters on the algorithm's performance are the main objectives of our study. Moreover, the impact of the different block and grid sizes was checked. To ensure comparability of the results, extensive tests have been carried out using the multi-swarm version designed for the GPU and the mono-swarm version designed for the CPU platform. The results show that the proposed multi-swarm Bees Algorithm algorithm for the CUDA platform gives considerable acceleration of the calculations, but often requires the larger size of the neighbourhood.

Journal of Artificial Intelligence and Soft Computing ResearchVol. 17(1)
AGH University of Krakow (PL)
Openalex Percentile: Top 12%
Belt Conveyor Systems Engineering
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Multi-Swarm Bees Algorithm with GPU Computing for Belt Conveyor Production System — Wojciech Chmiel, Joanna Kwiecień, et al. · Journal of Artificial Intelligence and Soft Computing Research (2026) | TGRS Research Map | TGRS