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Explaining Adaptation in Genetic Algorithms With Uniform Crossover: The Hyperclimbing Hypothesis
, 2012 The hyperclimbing hypothesis is a hypothetical explanation for adaptation in genetic algorithms with uniform crossover (UGAs). Hyperclimbing is an intuitive, general-purpose, non-local search heuristic applicable to discrete product spaces with rugged or
Burjorjee, Keki M.
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Variable grouping in multivariate time series via correlation [PDF]
, 2001 The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be huge.
Liu, X, Swift, S, Tucker, A
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Genetic algorithm design of neural network and fuzzy logic controllers [PDF]
, 2000 Genetic algorithm design of neural network and fuzzy logic ...
Chiu, K. S., Hunter, Andrew
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Elitist Schema Overlays: A Multi-Parent Genetic Operator [PDF]
, 2013 Genetic Algorithms are programs inspired by natural evolution used to solve difficult problems in Mathematics and Computer Science. The theoretical foundations of Genetic Algorithms, the schema theorem and the building-block hypothesis, state that the ...
Liffiton, Faculty Advisor, Mark +1 more
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XML-based genetic rules for scene boundary detection in a parallel processing environment [PDF]
, 2007 Genetic programming is based on Darwinian evolutionary theory that suggests that the best solution for a problem can be evolved by methods of natural selection of the fittest organisms in a population.
Angelides, MC, Parmar, MJ
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A simple two-module problem to exemplify building-block assembly under crossover
, 2004 Theoretically and empirically it is clear that a genetic algorithm with crossover will outperform a genetic algorithm without crossover in some fitness landscapes, and vice versa in other landscapes.
D. Wolpert +17 more
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Generalized disjunction decomposition for evolvable hardware [PDF]
, 2006 Evolvable hardware (EHW) refers to self-reconfiguration hardware design, where the configuration is under the control of an evolutionary algorithm (EA).
Kalganova, T, Lambert, C, Stomeo, E
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PDGA: The primal-dual genetic algorithm [PDF]
, 2003 Copyright @ 2003 IOS PressGenetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. Hence, incorporating mechanisms used in nature may improve the performance of GAs.
Yang, S
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IEEE AccessIn this study, we built a large-scale real-world dataset for further exploration of the Dynamic Flexible Job Shop Scheduling Problem (FJSSP) in a complex production environment that was developed and conducted based on a Genetic Adaptive Scheduling ...
Masmur Tarigan +3 more
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Effective Fitness Landscapes for Evolutionary Systems
, 1999 In evolution theory the concept of a fitness landscape has played an important role, evolution itself being portrayed as a hill-climbing process on a rugged landscape.
Stephens, C. R.
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