diagonalization

diagonalization - Genetic Algorithms in Chemistry Steven K...

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Genetic Algorithms in Chemistry Steven K. Burger October 2002
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Global Optimization The GA is not good for local search Doesn’t use derivative information Gradient is important for local searching
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Simplex vs. Quasi Newton
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Simplex vs. Quasi Newton
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Darwinian Evolution Survival of the Fittest Diversity of Species Scarce Resources
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Chromosomes of Information Variables represented as binary numbers Phenotype is fitness value x = x min + (x max -x min )d/(2 n -1) n = # of bits d = decimal value of gene J. H. Holland Sci Am. 267, July 1992, p.22
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Mutation Crossover J. H. Holland Sci Am. 267, July 1992, p.22
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Crossover, Mutation & Elitism
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Crossover Trouble
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Flowchart of the GA
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Selection Methods 1. Roulette Wheel Fitness scaled as a probability Rank 2. Tournament Binary Tertiary J. H. Holland Sci Am. 267, July 1992
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Number of Evaluations (Population Size) x (Number of Generations) Larmackian Evolution Inheritance of Acquired Characteristics. J. H. Holland Sci Am. 267, July 1992, p.22
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This note was uploaded on 10/19/2011 for the course CHEM 83 taught by Professor Bonk,j during the Spring '08 term at Duke.

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diagonalization - Genetic Algorithms in Chemistry Steven K...

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