output
20122025
most citedCuckoo Search: Recent Advances and Applications

1.1k citations

Showing cs.NEShow all

8 papers · 1 filter

cs.NE202411 cited

A Generalized Evolutionary Metaheuristic (GEM) Algorithm for Engineering Optimization

Xin-She Yang

Many optimization problems in engineering and industrial design applications can be formulated as optimization problems with highly nonlinear objectives, subject to multiple comple…

cs.NE2024

Parameter Tuning of the Firefly Algorithm by Standard Monte Carlo and Quasi-Monte Carlo Methods

Geethu Joy, Christian Huyck, Xin-She Yang

Almost all optimization algorithms have algorithm-dependent parameters, and the setting of such parameter values can significantly influence the behavior of the algorithm under con…

cs.NE20248 cited

Nature-Inspired Algorithms in Optimization: Introduction, Hybridization and Insights

Xin-She Yang

Many problems in science and engineering are optimization problems, which may require sophisticated optimization techniques to solve. Nature-inspired algorithms are a class of meta…

cs.NE20219 cited

A Nature-Inspired Feature Selection Approach based on Hypercomplex Information

Gustavo H. de Rosa, João Paulo Papa, Xin-She Yang

Feature selection for a given model can be transformed into an optimization task. The essential idea behind it is to find the most suitable subset of features according to some cri…

cs.NE201940 cited

Multi-Species Cuckoo Search Algorithm for Global Optimization

Xin-She Yang, Suash Deb, Sudhanshu K Mishra

Many optimization problems in science and engineering are highly nonlinear, and thus require sophisticated optimization techniques to solve. Traditional techniques such as gradient…

cs.NE201666 cited

Random-Key Cuckoo Search for the Travelling Salesman Problem

Aziz Ouaarab, B. Ahiod, Xin-She Yang

Combinatorial optimization problems are typically NP-hard, and thus very challenging to solve. In this paper, we present the random key cuckoo search (RKCS) algorithm for solving t…