{"ID":2882150,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.14982","arxiv_id":"2510.14982","title":"cuAPO: A CUDA-based Parallelization of Artificial Protozoa Optimizer","abstract":"Metaheuristic algorithms are widely used for solving complex problems due to their ability to provide near-optimal solutions. But the execution time of these algorithms increases with the problem size and/or solution space. And, to get more promising results, we have to execute these algorithms for a large number of iterations, requiring a large amount of time and this is one of the main issues found with these algorithms. To handle the same, researchers are now-a-days working on design and development of parallel versions of state-of-the-art metaheuristic optimization algorithms. We, in this paper, present a CUDA-based parallelization of state-of-the-art Artificial Protozoa Optimizer leveraging GPU acceleration. We implement both the existing sequential version and the proposed parallel version of Artificial Protozoa Optimizer for a performance comparison. Our experimental results calculated over a set of CEC2022 benchmark functions demonstrate a significant performance gain i.e. up to 6.7 times speed up is achieved with proposed parallel version. We also use a real world application, i.e., Image Thresholding to compare both algorithms.","short_abstract":"Metaheuristic algorithms are widely used for solving complex problems due to their ability to provide near-optimal solutions. But the execution time of these algorithms increases with the problem size and/or solution space. And, to get more promising results, we have to execute these algorithms for a large number of it...","url_abs":"https://arxiv.org/abs/2510.14982","url_pdf":"https://arxiv.org/pdf/2510.14982v2","authors":"[\"Henish Soliya\",\"Anugrah Jain\"]","published":"2025-08-14T04:44:29Z","proceeding":"cs.NE","tasks":"[\"cs.NE\",\"cs.AI\",\"cs.ET\"]","methods":"[]","has_code":false}