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Evolutionary algorithms in theory and practice
TLDR
In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming within a unified framework, thereby clarifying the similarities and differences of these methods.About:
The article was published on 1996-01-01 and is currently open access. It has received 2679 citations till now. The article focuses on the topics: Evolutionary music & Evolutionary programming.read more
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Stellar structure modeling using a parallel genetic algorithm for objective global optimization
T. S. Metcalfe,P. Charbonneau +1 more
TL;DR: In this article, a fully parallel and distributed hardware/software implementation of the generalized optimization subroutine PIKAIA, which utilizes a genetic algorithm to provide an objective determination of the globally optimal parameters for a given model against an observational data set, is presented.
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Efficient Differential Evolution algorithms for multimodal optimal control problems
TL;DR: The results show that within the class of evolutionary methods, Differential Evolution algorithms are very robust, effective and highly efficient in solving the studied class of optimal control problems and are able of mitigating the drawback of long computation times commonly associated with Evolutionary algorithms.
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Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability
TL;DR: This paper analyzes the rule classification model based on decision trees using a training selected set via evolutionary stratified instance selection to face the scaling problem that appears in the evaluation of large size data sets, and the trade off interpretability-precision of the generated models.
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Evolving better population distribution and exploration in evolutionary multi-objective optimization
TL;DR: Two features that enhance the optimization ability of multi-objective evolutionary algorithms are presented: a variant of the mutation operator that adapts the mutation rate along the evolution process to maintain a balance between the introduction of diversity and local fine-tuning and an enhanced exploration strategy that encourages the exploration towards less populated areas and hence achieves better discovery of gaps in the generated front.
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Object-Oriented Programming Applied to the Finite Element Method Part II. Application to Material Behaviors
TL;DR: This paper examines the application of C++ design patterns to the development of material constitutives equations to be used in finite element simulation softwares and comes up with an integrated approach to theDevelopment of new constitutive equations for structural computations.