Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Learning Bayesian networks with local structure
Learning in graphical models
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning
Phase transition in a random NK landscape model
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
An analysis of phase transition in NK landscapes
Journal of Artificial Intelligence Research
Hierarchical BOA solves ising spin glasses and MAXSAT
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Genetic algorithms on NK-landscapes: effects of selection, drift, mutation, and recombination
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
The computational complexity of N-K fitness functions
IEEE Transactions on Evolutionary Computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
NK landscapes, problem difficulty, and hybrid evolutionary algorithms
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Network crossover performance on NK landscapes and deceptive problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Performance of network crossover on NK landscapes and spin glasses
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Investigating vesicular selection
Applied Soft Computing
Geometric generalization of the nelder-mead algorithm
EvoCOP'10 Proceedings of the 10th European conference on Evolutionary Computation in Combinatorial Optimization
Evolving NK-complexity for evolutionary solvers
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Maximizing the number of polychronous groups in spiking networks
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Adaptation of a multiagent evolutionary algorithm to NK landscapes
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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This study analyzes performance of several genetic and evolutionary algorithms on randomly generated NK fitness landscapes with various values of n and k. A large number of NK problem instances are first generated for each n and k, and the global optimum of each instance is obtained using the branch-and-bound algorithm. Next, the hierarchical Bayesian optimization algorithm (hBOA), the univariate marginal distribution algorithm (UMDA), and the simple genetic algorithm (GA) with uniform and two-point crossover operators are applied to all generated instances. Performance of all algorithms is then analyzed and compared, and the results are discussed.