1.1k citations · 1.5k across the 11 of their papers we have counts for
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Bat Algorithm is Better Than Intermittent Search Strategy
Xin-She Yang, Suash Deb, Simon Fong
The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm c…
Cuckoo Search: Recent Advances and Applications
Xin-She Yang, Suash Deb
Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and CS is efficient in solving global optimization problems. In this paper, we review the funda…
A Framework for Self-Tuning Optimization Algorithm
Xin-She Yang, Suash Deb, M. Loomes +1
The performance of any algorithm will largely depend on the setting of its algorithm-dependent parameters. The optimal setting should allow the algorithm to achieve the best perfor…
Two-Stage Eagle Strategy with Differential Evolution
Xin-She Yang, Suash Deb
Efficiency of an optimization process is largely determined by the search algorithm and its fundamental characteristics. In a given optimization, a single type of algorithm is used…
Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications
Xin-She Yang, Suash Deb, Simon Fong
Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resource…
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…