Enhancing the cuckoo search with levy flight through population estimation

Mohd Nawi, Nazri and Shahuddin, Shah Liyana and Rehman, Muhammad Zubair and Khan, Abdullah (2016) Enhancing the cuckoo search with levy flight through population estimation. ARPN Journal of Engineering and Applied Sciences, 11 (22). pp. 13232-13240. ISSN 1819-6608

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Abstract

This paper proposed the use of population estimation in a new meta-heuristic called Cuckoo search (CS) algorithm to minimize the training error, achieve fast convergence rate and to avoid local minimum problem. The CS algorithm which imitates the cuckoo bird’s search behavior for finding the best nest has been applied independently to solve several engineering design optimization problems based on cuckoo bird’s behavior. The algorithm is tested on five benchmark functions such as Ackley function, Griewank function, Rastrigin function, Rosenbrock function and Schwefel function. The performance of the proposed algorithm was compared with Particle Swarm Optimization (PSO), Wolf Search Algorithm (WSA) and Artificial Bee Colony (ABC). The simulation results show that the CS with Levy flight out performs PSO, WSA and ABC, when the cuckoo population is varied.

Item Type:	Article
Uncontrolled Keywords:	meta-heuristics; cuckoo search; levy flight, optimization.
Subjects:	Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions:	Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User:	Mrs. Mashairani Ismail
Date Deposited:	02 Dec 2021 02:35
Last Modified:	02 Dec 2021 02:35
URI:	http://eprints.uthm.edu.my/id/eprint/4295

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