Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Niching methods for genetic algorithms
Niching methods for genetic algorithms
Recent approaches to global optimization problems through Particle Swarm Optimization
Natural Computing: an international journal
A species conserving genetic algorithm for multimodal function optimization
Evolutionary Computation
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Lévy flights, non-local search and simulated annealing
Journal of Computational Physics
A sequential niche technique for multimodal function optimization
Evolutionary Computation
Introduction to Mathematical Optimization: From Linear Programming to Metaheuristics
Introduction to Mathematical Optimization: From Linear Programming to Metaheuristics
A bi-criterion approach to multimodal optimization: self-adaptive approach
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Evolutionary programming using mutations based on the Levy probability distribution
IEEE Transactions on Evolutionary Computation
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution
IEEE Transactions on Evolutionary Computation
Bio-inspired computation: success and challenges of IJBIC
International Journal of Bio-Inspired Computation
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Modern engineering and scientific optimisation problems are becoming complicated. In order to cope with the increasing level of difficulty of these problems, optimisation methods are required to find more than one solution to these problems. The aim of this paper is to gain an insight into the ability of cuckoo search to locate more than one solution for multimodal problems. We also study the performance of this algorithm in the additive white Gaussian noise. Numerical results are presented to show that the cuckoo search algorithm can successfully locate multiple solutions in both non-noise and additive white Gaussian noise with relatively high degree of accuracy.