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An introduction and survey of estimation of distribution algorithms
TLDR
Abstract Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. Expand
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Influence of selection and replacement strategies on linkage learning in BOA
TLDR
The Bayesian optimization algorithm (BOA) uses Bayesian networks to learn linkages between the decision variables of an optimization problem. Expand
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A Survey of Estimation of Distribution Algorithms
Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promisingExpand
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Analyzing Probabilistic Models in Hierarchical BOA
TLDR
The hierarchical Bayesian optimization algorithm (hBOA) can solve nearly decomposable and hierarchical problems of bounded difficulty in a robust and scalable manner by building and sampling probabilistic models of promising solutions. Expand
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Using Previous Models to Bias Structural Learning in the Hierarchical BOA
TLDR
We propose two approaches to biasing model building in the hierarchical Bayesian optimization algorithm (hBOA) based on knowledge automatically learned from previous hBOA runs on similar problems. Expand
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Pairwise and problem-specific distance metrics in the linkage tree genetic algorithm
TLDR
The linkage tree genetic algorithm (LTGA) identifies linkages between problem variables using an agglomerative hierarchical clustering algorithm and linkage trees. Expand
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Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap
TLDR
This paper presents a class of NK landscapes with nearest-neighbor interactions and tunable overlap. Expand
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Network crossover performance on NK landscapes and deceptive problems
TLDR
This paper describes a method to build a network crossover operator that can be used in a GA to easily incorporate problem-specific knowledge. Expand
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Intelligent bias of network structures in the hierarchical BOA
TLDR
We propose an approach to bias the building of Bayesian network models in the hierarchical Bayesian optimization algorithm (hBOA) using information gathered from models generated during previous hBOA runs on similar problems. Expand
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Estimation of Distribution Algorithms
TLDR
Estimation of distribution algorithms (EDA s) guide the search for the optimum by building explicit probabilistic models of promising candidate solutions. Expand
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