Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
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
Learning probability distributions in continuous evolutionary algorithms– a comparative review
Natural Computing: an international journal
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Optimization in continuous domain by real-coded estimation of distribution algorithm
Design and application of hybrid intelligent systems
On the importance of diversity maintenance in estimation of distribution algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
The correlation-triggered adaptive variance scaling IDEA
Proceedings of the 8th annual conference on Genetic and evolutionary computation
SDR: a better trigger for adaptive variance scaling in normal EDAs
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Estimation of fitness landscape contours in EAs
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Connection Science - Evolutionary Learning and Optimisation
Why one must use reweighting in estimation of distribution algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Efficient natural evolution strategies
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Truncation selection and Gaussian EDA: bounds for sustainable progress in high-dimensional spaces
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Cumulative step length adaptation for evolution strategies using negative recombination weights
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
When do heavy-tail distributions help?
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
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Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains are surveyed in this article. The similarities and differences among them are emphasized and it is shown that they all can be described in a common framework of stochastic local search -- a class of methods previously defined mainly for combinatorial problems. Based on the lessons learned from the surveyed algorithms, a set of algorithm features (or, questions to be answered) is extracted. An algorithm designer can take advantage of these features and by deciding on each of them, she can construct a novel algorithm. A few examples in this direction are shown.