A comprehensive review of firefly algorithms
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The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice as mentioned in this paper, and many problems from various areas have been successfully solved using the Firefly algorithm and its variants.Abstract:
The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved using the firefly algorithm and its variants. In order to use the algorithm to solve diverse problems, the original firefly algorithm needs to be modified or hybridized. This paper carries out a comprehensive review of this living and evolving discipline of Swarm Intelligence, in order to show that the firefly algorithm could be applied to every problem arising in practice. On the other hand, it encourages new researchers and algorithm developers to use this simple and yet very efficient algorithm for problem solving. It often guarantees that the obtained results will meet the expectations.read more
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Book ChapterDOI
Introduction to Algorithms
TL;DR: This chapter provides an overview of the fundamentals of algorithms and their links to self-organization, exploration, and exploitation.
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Nature-Inspired Optimization Algorithms
TL;DR: This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences, and researchers and engineers as well as experienced experts will also find it a handy reference.
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A novel nature-inspired algorithm for optimization: Squirrel search algorithm
TL;DR: This optimizer imitates the dynamic foraging behaviour of southern flying squirrels and their efficient way of locomotion known as gliding and provides more accurate solutions with high convergence rate as compared to other existing optimizers.
Posted Content
A Brief Review of Nature-Inspired Algorithms for Optimization
TL;DR: A relatively comprehensive list of all the algorithms based on swarm intelligence, bio-inspired, physics-based and chemistry-based, depending on the sources of inspiration, that have become popular tools for solving real-world problems.
Journal ArticleDOI
A survey on new generation metaheuristic algorithms
TL;DR: In this survey, fourteen new and outstanding metaheuristics that have been introduced for the last twenty years other than the classical ones such as genetic, particle swarm, and tabu search are distinguished.
References
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Rainer Storn,Kenneth Price +1 more
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