IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization

Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization
View Sample PDF
Author(s): Pauline Ong (Universiti Tun Hussein Onn Malaysia, Malaysia)and S. Kohshelan (Universiti Tun Hussein Onn Malaysia, Malaysia)
Copyright: 2016
Pages: 24
Source title: Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics
Source Author(s)/Editor(s): Pandian Vasant (University of Technology Petronas, Malaysia), Gerhard-Wilhelm Weber (Middle East Technical University, Turkey)and Vo Ngoc Dieu (Ho Chi Minh City University of Technology, Vietnam)
DOI: 10.4018/978-1-4666-9644-0.ch026

Purchase

View Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization on the publisher's website for pricing and purchasing information.

Abstract

A new optimization algorithm, specifically, the cuckoo search algorithm (CSA), which inspired by the unique breeding strategy of cuckoos, has been developed recently. Preliminary studies demonstrated the comparative performances of the CSA as opposed to genetic algorithm and particle swarm optimization, however, with the competitive advantage of employing fewer control parameters. Given enough computation, the CSA is guaranteed to converge to the optimal solutions, albeit the search process associated to the random-walk behavior might be time-consuming. Moreover, the drawback from the fixed step size searching strategy in the inner computation of CSA still remain unsolved. The adaptive cuckoo search algorithm (ACSA), with the effort in the aspect of integrating an adaptive search strategy, was attached in this study. Its beneficial potential are analyzed in the benchmark test function optimization, as well as engineering optimization problem. Results showed that the proposed ACSA improved over the classical CSA.

Related Content

Pawan Kumar, Mukul Bhatnagar, Sanjay Taneja. © 2024. 26 pages.
Kapil Kumar Aggarwal, Atul Sharma, Rumit Kaur, Girish Lakhera. © 2024. 19 pages.
Mohammad Kashif, Puneet Kumar, Sachin Ghai, Satish Kumar. © 2024. 15 pages.
Manjit Kour. © 2024. 13 pages.
Sanjay Taneja, Reepu. © 2024. 19 pages.
Jaspreet Kaur, Ercan Ozen. © 2024. 28 pages.
Hayet Kaddachi, Naceur Benzina. © 2024. 25 pages.
Body Bottom