Abstract
Recent trend of research is to hybridize two and more algorithms to obtain superior solution in the field of optimization problems. In this context, a new technique hybrid particle swarm optimization (PSO)–whale optimizer (WOA) is exercised on some unconstraint benchmark test functions. Hybrid PSO–WOA is a combination of PSO used for exploitation phase and WOA for exploration phase in uncertain environment. Analysis of competitive results obtained from PSO–WOA validates its effectiveness compared to standard PSO and WOA algorithm.
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Trivedi, I.N., Jangir, P., Kumar, A., Jangir, N., Totlani, R. (2018). A Novel Hybrid PSO–WOA Algorithm for Global Numerical Functions Optimization. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-10-3773-3_6
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DOI: https://doi.org/10.1007/978-981-10-3773-3_6
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