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A Hybrid Genetic Algorithm for School Timetabling
2002Hybrid Genetic Algorithms apply so called hybrid or repair operators or include problem specific knowledge about the problem domain in their mutation and crossover operators. These operators use local search to repair or avoid illegal or unsuitable assignments or just to improve the quality of the solutions already found.Those Hybrid Genetic Algorithms
Peter Wilke +2 more
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Production of ‘hybrid’ antibiotics by genetic engineering
Nature, 1985The recent development of molecular cloning systems in Streptomyces has made possible the isolation of biosynthetic genes for some of the many antibiotics produced by members of this important genus of bacteria. Such clones can now be used to test the idea that novel antibiotics could arise through the transfer of biosynthetic genes between ...
D A, Hopwood +8 more
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Hybrid Dysfunction: Population Genetic and Quantitative Genetic Perspectives
The American Naturalist, 2008In the wake of seminal work by Dobzhansky and Muller, hybrid dysfunction is usually attributed to incompatible mutations in different genes arising in different populations. This Dobzhansky-Muller (D-M) model is among the most important contributions of theoretical population genetics.
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A hybrid genetic algorithm with the Baldwin effect
Information Sciences, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Quan Yuan, Feng Qian 0004, Wenli Du
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2014
Real coded Genetic Algorithms (GAs) are the most effective and popular techniques for solving continuous optimization problems. In the recent past, researchers used the Laplace Crossover (LX) and Power Mutation (PM) in the GA cycle (namely LX-PM) efficiently for solving both constrained and unconstrained optimization problems.
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Real coded Genetic Algorithms (GAs) are the most effective and popular techniques for solving continuous optimization problems. In the recent past, researchers used the Laplace Crossover (LX) and Power Mutation (PM) in the GA cycle (namely LX-PM) efficiently for solving both constrained and unconstrained optimization problems.
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Hybrid Genetic Algorithms for a Rostering Problem
Software: Practice and Experience, 1996Hybrid Genetic Algorithms are described for a large-size real-life rostering problem (railway workers' job scheduling and roster optimization). The new algorithm uses an order-based representation which encodes as a chromosome the list of job units to schedule. First, a greedy algorithm is considered, which uses a randomly generated job units list, and
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Rice Artificial Hybridization for Genetic Analysis
2012Artificial hybridization has probably been practiced since ancient time; however, the science of genetics did not initiate until Gregor Mendel conducted a series of crosses between different pure lines of garden pea and made careful observations and systematical analyses of their offspring.
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Genetic Testing in Prostate Cancer Management: Considerations Informing Primary Care
Ca-A Cancer Journal for Clinicians, 2022Todd M Morgan +2 more
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