Mathematical Analysis of Nature-Inspired Algorithms

  • Xin-She YangEmail author
Part of the Studies in Computational Intelligence book series (SCI, volume 744)


Nature-inspired algorithms are a class of effective tools for solving optimization problems and these algorithms have good properties such as simplicity, flexibility and high efficiency. Despite their popularity in practice, a mathematical framework is yet to be developed to analyze these algorithms theoretically. This work intends to analyze nature-inspired algorithms both qualitatively and quantitatively. We briefly outline the links between self-organization and algorithms, and then analyze algorithms using Markov chain theory, dynamic system and other methods. This can serve as a basis for building a multidisciplinary framework for algorithm analysis.


Algorithm Bat algorithm Cuckoo search Differential evolution Firefly algorithm Flower pollination algorithm Particle swarm optimization Metaheuristics Nature-inspired computation Optimization Self-organization Swarm intelligence 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.School of Science and TechnologyMiddlesex UniversityLondonUK

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