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In mathematical optimization, the firefly algorithm is a metaheuristic proposed by Xin-She Yang and inspired by the flashing behavior of fireflies. [1] Algorithm. In pseudocode the algorithm can be stated as: Begin . 1) Objective function: ; . 2) Generate an initial population of fireflies ;.
Learn about the firefly algorithm (FA), a nature-inspired optimization algorithm based on the flashing behavior of fireflies. Find out how FA has been applied in various fields, such as image processing, network reconfiguration, and traveling salesman problem, and compare its performance with other algorithms.
Feb 20, 2023 · Learn about the firefly algorithm, a metaheuristic optimization technique based on the flashing behavior of fireflies. See the pseudocode, implementation steps and examples of the algorithm, and explore its use cases in various fields.
Sep 29, 2020 · This paper presents a comprehensive review of firefly algorithm (FA), a meta-heuristic optimization technique inspired by firefly behaviour. It discusses the characteristics, variants, applications, and future directions of FA and its hybrid versions.
- Vijay Kumar, Dinesh Kumar
- 2021
Apr 9, 2020 · The Firefly Algorithm: An Introduction. April 2020. Authors: Xin-She Yang. Middlesex University, UK. References (4) Abstract. This presentation introduces the standard Firefly Algorithm...
- Xin-She Yang
Nov 14, 2020 · Learn how fireflies' flashing behavior inspires a nature-inspired algorithm for solving complex optimization problems. This chapter explains the principles, advantages, disadvantages and applications of the firefly algorithm with examples and illustrations.
Firefly Algorithms. Xin-She Yang, in Nature-Inspired Optimization Algorithms, 2014. 8.4.1 FA Variants. The standard FA is very efficient, but there is still room for improvement. In the last five years, researchers have tried various ways to enhance the performance and speed up the convergence of the firefly algorithm.
