“ Genetic algorithms are stochastic search and optimization algorithms based on the mechanics of natural selection and natural genetics subject to survival of the fittest. The algorithm iteratively transforms a set (population) of mathematical objects (string structures), each with an associated fitness value, into a new population of offspring objects using crossover and mutation ”
Stochastic Search Algorithm
Natural Selection and Genetics Operators
Darwin’s Theory (Survival of the Fittest)
Evolutionary process
Population
Crossover
Mutation
02/05/10 14:07 Genetic Algorithms – A gentle Introduction Definition of Genetic Algorithms
Test each solution in the set (rank them) Remove some bad solutions from set Duplicate some good solutions make small changes to some of them
Until
best solution is good enough
02/05/10 14:07 Genetic Algorithms – A gentle Introduction Basic Idea
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local global I am not at the top. My high is better! I am at the top My Height is .. I will continue 02/05/10 14:07 Genetic Algorithms – A gentle Introduction Search for Optimization
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction Optimization
“ Genetic algorithms are stochastic search and optimization algorithms based on the mechanics of natural selection and natural genetics subject to survival of the fittest. The algorithm iteratively transforms a set (population) of mathematical objects (string structures), each with an associated fitness value, into a new population of offspring objects using crossover and mutation ”
02/05/10 14:07 Genetic Algorithms – A gentle Introduction Definition of Genetic Algorithms
Can we imagine natural world as a result of many iterations in a grand optimization algorithm ?
02/05/10 14:07 Genetic Algorithms – A gentle Introduction Background of GAs
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction
Genes are the basic “instructions” for building an organism
A chromosome is a sequence of genes
Biologists distinguish between an organism’s
genotype (the genes and chromosomes) and its
phenotype (what the organism actually is like)
Similarly, “genes” may describe a possible solution to a problem, without actually being the solution
Natural World
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction
Human body is made up of trillions of cells. Each cell has a core structure (nucleus) that contains chromosomes.
Each chromosome is made up of tightly coiled strands of deoxyribonucleic acid (DNA). Genes are segments of DNA that determine specific traits, such as eye or hair color. A human have more than 20,000 genes.
“ Genetic algorithms are stochastic search and optimization algorithms based on the mechanics of natural selection and natural genetics subject to survival of the fittest. The algorithm iteratively transforms a set (population) of mathematical objects (string structures), each with an associated fitness value, into a new population of offspring objects using crossover and mutation ”
02/05/10 14:07 Genetic Algorithms – A gentle Introduction Definition of Genetic Algorithms
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Randomly generate a population of potential solutions Evaluate fitness of population members Select two parents from population based on fitness Produce two children Evaluate children Crossover and mutation Is solution "Good“? Output best solution found Multiple Repeats in one iteration No Yes Genetic Algorithms Flowchart
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction Phenotype x Genotype g Gen. Phen. Mapping Population Objective Function f i Population Pop Cross over Mutation Genotype g Initial Population Create an initial population of random individuals
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction
Simple problem: max x 2 over {0,1,…,31}
GA approach:
Representation: binary code, e.g. 01101 13
Population size: 4
1-point Crossover, bitwise mutation
Roulette wheel selection
Random initialization
One generational cycle will be shown
A Simple Example of Genetic Algorithms 16 8 4 2 1 13 0 1 1 0 1 24 1 1 0 0 0 8 0 1 0 0 0
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction A Simple Example of Genetic Algorithms
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction 2 1 n 3 Area is Proportional to fitness value 4 Roulette Wheel Selection Individual i will have a probability to be chosen
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction 10011 101 11101 000 10011 000 Parent A Child of A and B Parent B Crossover Operator A Simple Example of Genetic Algorithms
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02/05/10 14:07 Genetic Algorithms – A gentle Introduction A Simple Example of Genetic Algorithms
“ Genetic algorithms are stochastic search and optimization algorithms based on the mechanics of natural selection and natural genetics subject to survival of the fittest. The algorithm iteratively transforms a set (population) of mathematical objects (string structures), each with an associated fitness value, into a new population of offspring objects using crossover and mutation ”
02/05/10 14:07 Genetic Algorithms – A gentle Introduction Definition of Genetic Algorithms
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