most citedA New Metaheuristic Bat-Inspired Algorithm

312 citations · 704 across the 16 of their papers we have counts for

collaborators
Showing math.OCShow all

8 papers · 1 filter

math.OC2010108 cited

Test Problems in Optimization

Xin-She Yang

Test functions are important to validate new optimization algorithms and to compare the performance of various algorithms. There are many test functions in the literature, but ther…

math.OC2010137 cited

Engineering Optimisation by Cuckoo Search

Xin-She Yang, Suash Deb

A new metaheuristic optimisation algorithm, called Cuckoo Search (CS), was developed recently by Yang and Deb (2009). This paper presents a more extensive comparison study using so…

math.OC2010312 cited

A New Metaheuristic Bat-Inspired Algorithm

Xin-She Yang

Metaheuristic algorithms such as particle swarm optimization, firefly algorithm and harmony search are now becoming powerful methods for solving many tough optimization problems. I…

math.OC201060 cited

Eagle Strategy Using Lévy Walk and Firefly Algorithms For Stochastic Optimization

Xin-She Yang, Suash Deb

Most global optimization problems are nonlinear and thus difficult to solve, and they become even more challenging when uncertainties are present in objective functions and constra…

math.OC20101 cited

Biology-Derived Algorithms in Engineering Optimization

Xin-She Yang

Biology-derived algorithms are an important part of computational sciences, which are essential to many scientific disciplines and engineering applications. Many computational meth…

math.OC201035 cited

Harmony Search as a Metaheuristic Algorithm

Xin-She Yang

This first chapter intends to review and analyze the powerful new Harmony Search (HS) algorithm in the context of metaheuristic algorithms. I will first outline the fundamental ste…