A Comparative Study of Cuckoo Search and Flower Pollination Algorithm on Solving Global Optimization Problems

Purpose The purpose of this paper is to present a comparison between two well-known Levy-based meta-heuristics called cuckoo search (CS) and flower pollination algorithm (FPA). Design/methodology/approach Both the algorithms (Levy-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.