Genetic Algorithms

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

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

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.

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

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); }

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

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.

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

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Genetic Algorithms