Genetic Algorithms

Genetic Programming Representation of Chromosome Selection Procedure(pseudo code) Roulette Wheel procedure Java Genetic Algorithm library Python Genetic Algorithm library Vasanth Raja Chittampally 10IT05F http://www.vasanthexperiments .wordpress.com

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Representation of Chromosome

 private static class Chromosome { – – – – public double score; StringBuffer chromo= new StringBuffer(chromoLen * 4); // public Chromosome(int target) {  //  chromo.append(binString); // } } Vasanth Raja Chittampally www.vasanthexperiments .wordpress.com

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Roulette Wheel selection procedure

 A roulette wheel contains slots weighted in proportion to string fitness values.

 In the below code we see the select function returns the index value corresponding to the selected individual.

 Partial sum of the fitness values is accumulated in the real variable

partsum

–

rand=rand*sumfitness

Sum of the population fitnesses is multiplied by the normalized pseudorandom number.

Repeate-until

searches through the weighted roulette wheel until the partial sum is greater than or equal to the stopping point rand.

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Pseudo code of Selection process

 Function select(popsize, sumfitness, population) { – Begin  Partsum=0 j=0  rand= rand*sumfitness 

Repeat

–

j=j+1

–

partsum=partsum+pop[j].fitness

Until(partsum>=rand) or (j=popsize)

– Return individual number – Select=j end Vasanth Raja Chittampally www.vasanthexperiments .wordpress.com

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Java Selection Function

 private Chomosone selectMember(ArrayList l) { double tot=0.0; for (int x=l.size()-1;x>=0;x--) { double score = ((Chomosone)l.get(x)).score; tot+=score; } double rand1 = tot*rand.nextDouble(); double ttot=0.0; for (int x=l.size()-1;x>=0;x--) { Chomosone node = (Chomosone)l.get(x); ttot+=node.score; if (ttot>=rand1) { l.remove(x); return node; } } return (Chomosone)l.remove(l.size()-1); } 5

Java Genetic Algorithm Library

 http://jgap.sourceforge.net/  It provides basic genetic mechanisms that can be easily used to apply evolutionary principles to problem solutions  This contains the general purpose functions to be performed for Genetic algorithms  Good documentation is available  Set of examples were given in the above link with source code 6

Python Genetic Algorithms Library

 http://pyevolve.sourceforge.net/  Pyevolve was developed to be a

complete genetic algorithm framework written in pure python

.

 Good documentation is available  Set of examples were given in the above link with source code  http://www.freenet.org.nz/python/pygene/  Python based genetic algorithms library.

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References

 http://www.genetic-programming.org/  http://pyevolve.sourceforge.net

 http://gafp.sourceforge.net/  http://jgap.sourceforge.net/  http://amitksaha.wordpress.com/2009/12/16/ga-based sorting-bogosort-using-pyevolve/  http://amitksaha.wordpress.com/2009/12/16/ga-based sorting-bogosort-using-pyevolve/  http://pyevolve.sourceforge.net/examples.html#example 12-the-travelling-salesman-problem-tsp  http://www.geneticprogramming.com/ga 8

Queries ???

Vasanth Raja Chittampally 10IT05F www.vasanthexperiments .wordpress.com

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Thank you

Vasanth Raja Chittampally 10IT05F www.vasanthexperiments .wordpress.com

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