Lipschitzian optimization without the Lipschitz constant
Journal of Optimization Theory and Applications
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
A computationally efficient evolutionary algorithm for real-parameter optimization
Evolutionary Computation
Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
A population-based algorithm-generator for real-parameter optimization
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Adaptive Encoding: How to Render Search Coordinate System Invariant
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Preventing Premature Convergence in a Simple EDA Via Global Step Size Setting
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Solving the sorting network problem using iterative optimization with evolved hypermutations
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distribution
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
BBOB-benchmarking the generalized generation gap model with parent centric crossover
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Benchmarking the nelder-mead downhill simplex algorithm with many local restarts
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Benchmarking the NEWUOA on the BBOB-2009 function testbed
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Evolutionary-based iterative local search algorithm for the shortest common supersequence problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Six population-based methods for real-valued black box optimization are thoroughly compared in this article. One of them, Nelder-Mead simplex search, is rather old, but still a popular technique of direct search. The remaining five POEMS, G3PCX, Cauchy EDA, BIPOP-CMA-ES, and CMA-ES are more recent and came from the evolutionary computation community. The recently proposed comparing continuous optimizers COCO methodology was adopted as the basis for the comparison. The results show that BIPOP-CMA-ES reaches the highest success rates and is often also quite fast. The results of the remaining algorithms are mixed, but Cauchy EDA and POEMS are usually slow.