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

Wojciech Chmiel; Paweł Kolendo; Joanna Kwiecień

doi:10.2478/jaiscr-2026-0023

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

Journal of Artificial Intelligence and Soft Computing Research

Volume 17 (2027): Issue 1 (January 2027)

By: Wojciech Chmiel , Paweł Kolendo and Joanna Kwiecień

Open Access

|Jul 2026

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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Articles in this issue

DOI: https://doi.org/10.2478/jaiscr-2026-0023

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Language: English

Page range: 39 - 59

Submitted on: Jul 28, 2025

Accepted on: May 19, 2026

Published on: Jul 1, 2026

Published by: SAN University

In partnership with: Paradigm Publishing Services

Keywords:

CUDA,

quadratic assignment problem,

multi-swarm bees algorithm,

Belt Conveyor Production System (BCPS)

Related subjects:

Computer sciences,

Artificial intelligence,

Computer sciences,

Databases and data mining

© 2026 Wojciech Chmiel, Paweł Kolendo, Joanna Kwiecień, published by SAN University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 17 (2027): Issue 1 (January 2027)