A novel firefly algorithm with self-adaptive step strategy. (28th June 2019)

• Record Type: Journal Article
• Authors: Wang, Jing; Liu, Guiyuan
• Is Part Of: International journal of innovative computing and applications. Volume 10:Number 1(2019)
• Page Start: 18
• Page End: 26
• Publication Date: 2019-06-28
• Subjects: firefly algorithm -- random moving step -- meta-heuristic algorithm -- global optimisation; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

In the standard firefly algorithm, the random moving step is very important to the direction of the firefly movement, and the parameter alpha plays an important role in the random moving step. In this paper, we proposed a self-adaptive step strategy based on distance control in this paper, and we called it SASFA. Thirteen well-known benchmark functions are used to verify the performance of our proposed method; the computational results show that SASFA is more efficient than many other FA algorithms.