Book Chapter10.1007/978-3-642-29694-9_17
Bat Algorithm and Cuckoo Search: A Tutorial
Xin-She Yang
- 01 Jan 2013
- pp 421-434
56
TL;DR: This chapter briefly review two latest metaheuristics: bat algorithm and cuckoo search for global optimization, inspired by the echolocation of microbats and brood parasitism of some cuckoos.
read more
Abstract: Nature-inspired metaheuristic algorithms have attracted much attention in the last decade, and new algorithms have emerged almost every year with a vast, ever-expanding literature. In this chapter, we briefly review two latest metaheuristics: bat algorithm and cuckoo search for global optimization. Bat algorithm was proposed by Xin-She Yang in 2010, inspired by the echolocation of microbats, while cuckoo search was developed by Xin-She Yang and Suash Deb in 2009, inspired by the brood parasitism of some cuckoo species. Both algorithms have shown superiority over many other metaheuristics over a wide range of applications.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
•Book
Nature-Inspired Optimization Algorithms
Xin-She Yang
- 17 Feb 2014
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.
Bat algorithm: literature review and applications
Xin-She Yang,Xingshi He +1 more
TL;DR: A timely review of the bat algorithm and its new variants and a wide range of diverse applications and case studies are reviewed and summarised briefly here.
Bat Algorithm: Literature Review and Applications
TL;DR: A review of the bat algorithm and its variants can be found in this article, where a wide range of diverse applications and case studies are also reviewed and summarized briefly in the article.
371
Cuckoo Search and Firefly Algorithm
Xin-She Yang
- 01 Jan 2014
TL;DR: This chapter provides an overview of both cuckoo search and firefly algorithm as well as their latest developments and applications and analyzes these algorithms to gain insight into their search mechanisms and find out why they are efficient.
Modified cuckoo search algorithm with rough sets for feature selection
TL;DR: A modified cuckoo search algorithm that imitates the obligate brood parasitic behavior of some cuckoos species in combination with the Lévy flight behavior and can significantly improve the classification performance is presented.
184
References
Cuckoo Search via Lévy flights
Xin-She Yang,Suash Deb +1 more
- 01 Dec 2009
TL;DR: A new meta-heuristic algorithm, called Cuckoo Search (CS), is formulated, based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour ofSome birds and fruit flies, for solving optimization problems.
•Book
Nature-Inspired Metaheuristic Algorithms
Xin-She Yang
- 01 Feb 2008
TL;DR: This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms.
4.9K
A New Metaheuristic Bat-Inspired Algorithm
Xin-She Yang
- 23 Apr 2010
TL;DR: The Bat Algorithm as mentioned in this paper is based on the echolocation behavior of bats and combines the advantages of existing algorithms into the new bat algorithm to solve many tough optimization problems.
4.4K
•Posted Content
A New Metaheuristic Bat-Inspired Algorithm
TL;DR: The Bat Algorithm as mentioned in this paper is based on the echolocation behavior of bats and combines the advantages of existing algorithms into the new bat algorithm to solve many tough optimization problems.
Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems
TL;DR: The performance of the CS algorithm is further compared with various algorithms representative of the state of the art in the area and the optimal solutions obtained are mostly far better than the best solutions obtained by the existing methods.
2K
Related Papers (5)
Xin-She Yang,Suash Deb +1 more
- 01 Dec 2009
Xin-She Yang
- 23 Apr 2010