Abstract
With the increasing complexity and difficulty of practical problems, higher requirements are put forward to optimization techniques, especially the improvement on reliability and performance of meta-heuristic algorithm. In this paper, an improved arithmetic optimization algorithm (IAOA) is proposed, and it is compared with two algorithms—particle swarm optimization (PSO) and arithmetic optimization algorithm (AOA) on 13 benchmark functions. Experimental results show that the proposed algorithm performed better than the compared algorithms in solving particle problems in most cases.
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References
Abualigah, L., Hehab, M., Shinwan, M.: Salp swarm algorithm: a comprehensive survey. J. Neur. Comput. Appl. 32(15), 11195–11215 (2020)
Kennedy, J.: Particle swarm optimization. In: Sammut, C.I., Webb, G. (eds.) Proceedings of 1995 IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948 (2011)
Song, P.C., Pan, J.S., Chu, S.C.: A parallel compact cuckoo search algorithm for three-dimensional path planning. J. Appl. Soft Comput. 94 (2020)
Okwu, M., Tartibu, L.: Butterfly optimization algorithm. In: Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications, . Chapter: 105–114. Springer, Cham (2020)
Hu, P., Pan, J.S., Chu, S.C.: Improved binary grey wolf optimizer and its application for feature selection. J. Knowl.-Based Syst. 195 (2020)
Mirjalili, S., Lewis, A.: Adaptive gbest-guided gravitational search algorithm. J. Neur. Comput Appl. 25(7–8), 1569–1584 (2014)
Meshkat, M., Parhizgar, M.: A novel sine and cosine algorithm for global optimization. In: 2017 7th International Conference on Computer and Knowledge Engineering (ICCKE), vol. 96, pp. 120–133 (2017)
Abualigah, L., Diabat, A., Mirjalili, S.: The Arithmetic optimization algorithm. Comput. Methods Appl. Mech. Eng., 376 (2021)
Zhuang, J., Luo, H., Pan, T.-S., Pan, J.-S.: Improved flower pollination algorithm for the capacitated vehicle routing problem. J. Netw. Intell. 5(3), 141–156 (2020)
Trong, N., Jeng, P., Tsu, W., Thi, D., Trinh, N.: Node coverage optimization strategy based on ions motion optimization. J. Netw. Intell. 4(1), 1–9 (2019)
Acknowledgements
This work is funded by the Key Laboratory of Nondestructive Testing in Fuqing Branch of Fujian Normal University, Fujian Province, under grants # S2-KF1901.
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Wang, RB., Yin, S., Wang, WF., An, ZW., Xu, L. (2022). An Improved Arithmetic Optimization Algorithm with a Strategy Balancing Exploration and Exploitation. In: Wu, TY., Ni, S., Chu, SC., Chen, CH., Favorskaya, M. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. Smart Innovation, Systems and Technologies, vol 250. Springer, Singapore. https://doi.org/10.1007/978-981-16-4039-1_28
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DOI: https://doi.org/10.1007/978-981-16-4039-1_28
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