A comparative study of cuckoo search and flower pollination algorithm on solving global optimization problems. Issue 4 (20th November 2017)

• Record Type: Journal Article
• Authors: Abdel-Basset, Mohamed; Shawky, Laila A.; Sangaiah, Arun Kumar
• Is Part Of: Library hi tech. Volume 35:Issue 4(2017)
• Page Start: 588
• Page End: 601
• Publication Date: 2017-11-20
• Subjects: Optimization -- Metaheuristic -- Cuckoo search -- Flower pollination algorithm -- Lévy-based global search -- Local search; Library science -- Technological innovations -- Periodicals; Libraries -- Automation -- Periodicals; Information science -- Periodicals; 025.00285
• DOI: 10.1108/LHT-04-2017-0077
• Languages: English
• ISSNs: 0737-8831

Abstract

Abstract : Purpose: The purpose of this paper is to present a comparison between two well-known Lévy-based meta-heuristics called cuckoo search (CS) and flower pollination algorithm (FPA). Design/methodology/approach: Both the algorithms (Lévy-based meta-heuristics called CS and Flower Pollination) are tested on selected benchmarks from CEC 2017. In addition, this study discussed all CS and FPA comparisons that were included implicitly in other works. Findings: The experimental results show that CS is superior in global convergence to the optimal solution, while FPA outperforms CS in terms of time complexity. Originality/value: This paper compares the working flow and significance of FPA and CS which seems to have many similarities in order to help the researchers deeply understand the differences between both algorithms. The experimental results are clearly shown to solve the global optimization problem.