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Analysis of Firefly Algorithms and Automatic Parameter Tuning

Analysis of Firefly Algorithms and Automatic Parameter Tuning
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Author(s): Xin-She Yang (Middlesex University London, UK)
Copyright: 2015
Pages: 14
Source title: Emerging Research on Swarm Intelligence and Algorithm Optimization
Source Author(s)/Editor(s): Yuhui Shi (Southern University of Science and Technology (SUSTech), China)
DOI: 10.4018/978-1-4666-6328-2.ch002

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Abstract

Many metaheuristic algorithms are nature-inspired, and most are population-based. Particle swarm optimization is a good example as an efficient metaheuristic algorithm. Inspired by PSO, many new algorithms have been developed in recent years. For example, firefly algorithm was inspired by the flashing behaviour of fireflies. In this chapter, the authors analyze the standard firefly algorithm and study the chaos-enhanced firefly algorithm with automatic parameter tuning. They first compare the performance of these algorithms and then use them to solve a benchmark design problem in engineering. Results obtained by other methods are compared and analyzed. The authors also discuss some important topics for further research.

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