Chaos-enhanced flower pollination algorithms for global optimization

Article type: Research Article

Authors: Arora, Sankalap^{a; *} | Anand, Priyanka^b

Affiliations: [a] DAV University, Punjab, India | [b] Lovely Professional University, Punjab, India

Correspondence: [*] Corresponding author. Dr. Sankalap Arora, DAV University, Punjab, India. Tel.: +91 97790 39097; E-mail: [email protected].

Abstract: The flower pollination algorithm (FPA) is a recently developed meta-heuristic algorithm inspired by the pollination process of flowers. Similar to other meta-heuristic algorithms, it encounters two probable problems, i.e., entrapment in local optima and slow convergence speed, in solving challenging complex real world problems. Similar to the chaos in actual flower pollination process, this paper proposes new FPAs that employ chaotic maps for adjustment of parameters with the aim to improve the convergence rate and prevent the FPAs to get trapped on local optima. This is achieved by employing chaotic number generators every time, a random number is needed by the classical FPA. Two new chaotic FPAs have been proposed and various test problems are used for their performance evaluation. To check the effectiveness of the proposed algorithms, they are tested on various benchmark functions and engineering design problems with different characteristics having real world applications. The simulation results demonstrate that the chaotic maps are able to significantly boost the performance of FPAs.

Keywords: Flower pollination algorithm, chaos, global optimization, engineering design problems

DOI: 10.3233/JIFS-17708

Journal: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 6, pp. 3853-3869, 2017