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Performance Analysis of Tree Seed Algorithm for Small Dimension Optimization FunctionsBESKIRLI, M. |
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Author keywords
benchmark testing, algorithms, optimization, heuristic algorithms, optimization methods
References keywords
algorithm(22), optimization(17), tree(13), seed(13), systems(9), problems(5), improved(5), kiran(4), constrained(4), chen(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2020-05-31
Volume 20, Issue 2, Year 2020, On page(s): 65 - 72
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.02008
Web of Science Accession Number: 000537943500008
SCOPUS ID: 85087439628
Abstract
Tree-Seed Algorithm (TSA) simulates the growth of trees and seeds on a land. TSA is a method proposed to solve continuous optimization problems. Trees and seeds indicate possible solutions in the search space for optimization problems. Trees are planted in the ground at the beginning of the search and each tree produces several seeds during iterations. While the trees were selected randomly during seed formation, the tournament selection method was used and also hybridized by adding the C parameter, which is the acceleration coefficient calculated according to the size of the problem. In this study, continuous optimization problem has been solved by the hybrid method. First, the performance analyses of the five best known numerical benchmark functions have been done, in both TSA and hybrid method TSA with 2, 3, 4 and 5 dimensions, and 10-50 population numbers. After that, well-known algorithms in the literature like Particle Swarm Optimization (PSO), TSA, Artificial Bee Colony (ABC), Harmony Search (HS), as well as hybrid method TSA (HTSA) have been applied to twenty-four numerical benchmark functions and the performance analyses of algorithms have been done. Hopeful and comparable conclusions based on solution quality and robustness can be obtained with the hybrid method. |
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[1] An incremental tree seed algorithm for balancing local and global search behaviors in continuous optimization problems, Beşkirli, Mehmet, Neural Computing and Applications, ISSN 0941-0643, Issue 31, Volume 36, 2024.
Digital Object Identifier: 10.1007/s00521-024-10228-9 [CrossRef]
[2] An efficient tree seed inspired algorithm for parameter estimation of Photovoltaic models, Beşkirli, Ayşe, Dağ, İdiris, Energy Reports, ISSN 2352-4847, Issue , 2022.
Digital Object Identifier: 10.1016/j.egyr.2021.11.103 [CrossRef]
[3] Parameter extraction for photovoltaic models with tree seed algorithm, Beşkirli, Ayşe, Dağ, İdiris, Energy Reports, ISSN 2352-4847, Issue , 2023.
Digital Object Identifier: 10.1016/j.egyr.2022.10.386 [CrossRef]
[4] Advances in Tree Seed Algorithm: A Comprehensive Survey, Gharehchopogh, Farhad Soleimanian, Archives of Computational Methods in Engineering, ISSN 1134-3060, Issue 5, Volume 29, 2022.
Digital Object Identifier: 10.1007/s11831-021-09698-0 [CrossRef]
[5] Enhanced Tree-Seed Algorithm Solving Real-World Problems, Bujok, Petr, 2020 7th International Conference on Soft Computing & Machine Intelligence (ISCMI), ISBN 978-1-7281-7559-1, 2020.
Digital Object Identifier: 10.1109/ISCMI51676.2020.9311593 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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