Abstract
Optimization is a process in which the system is being modified so that the features can work more effectively or by finding any necessity execution. This process is conducted through maximizing and minimizing the parameters that are being involved in the problem. Many successful optimization approaches are available in the recent scenario; however, this research work focuses on cuckoo search technique. A new higher level procedure optimization algorithm called cuckoo search (CS) was developed by Yang and Deb in 2009. Cuckoo search is a swarm intelligence (SI) algorithm. Swarm intelligence techniques are those techniques that are being originated from the behavior of swarm. Cuckoo search algorithm is being inspired by the bird called cuckoo. It is the inspiration of brooding parasitism of cuckoo species and implemented successfully in many areas for optimization. This paper represents a brief review on CS algorithm along with the optimization process implementing some standard test functions. This research work highlights test function optimization for the non constraint function. This work may give an inspiration to apply the CS algorithm to solve the engineering design optimization problems.
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Sahoo, M.M., Dash, R., Rautray, R., Dash, R. (2021). Optimization Through Cuckoo Search with a Brief Review. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 153. Springer, Singapore. https://doi.org/10.1007/978-981-15-6202-0_53
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DOI: https://doi.org/10.1007/978-981-15-6202-0_53
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