gpdotnetv2.0 - darwin's theory of evolution in solving engineering problems by c#

8/10/2019 GpdotNETv2.0 - Darwin's theory of evolution in solving engineering problems by C#

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Thanks to all our sponsors,they made this possible!

Thanks to all our sponsors,they made this possible!


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GENETICALGORITHM

Genetic Algorithm (GA) is heuristic methodthat mimics the proces of natural selection.

GA represents population of strings(chromosomes) which encode posiblesolutions (phenotypes)

In GA every chromosom is defined withfixed size.

Most GA problems used chromsomes inform of string of binary numbers.


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GENETICPROGRAMMING

GP is variation of GA, with diferentChromosome sizes.

GP envolves computer programs,represented as tree structure.

Every tree contains: terminals and functions Inner nodes represent functions Outer nodes represent terminals


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GPFLOWCHART


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A COMPUTERPROGRAM IN C

int foo (int time){

int temp1, temp2;if (time > 10)

temp1 = 3;else

temp1 = 4;temp2 = temp1 + 1 + 2;return (temp2);

}


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OUTPUT OF CPROGRAMTime Output

0 6

1 6

2 6

3 6

4 6

5 6

6 6

7 6

8 6

9 6

10 6

11 7

12 7


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PROGRAM TREE

(+ 1 2 (IF (> TIME 10) 3 4))


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CREATING RANDOMPROGRAMS

Available functionsF = {+, -, *, %, IFLTE }

Available terminalsT = {X, Y, Random-Constants } The random programs are :

Of different sizes and shapes Syntactically valid Executable


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GP GENETICOPERATIONS

Reproduction Mutation Crossover (sexual recombination) Others


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MUTATIONOPERATION


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CROSSOVEROPERATION


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REPRODUCTION

OPERATION Select parent probabilisticallybased on fitness

Copy it (unchanged) into the nextgeneration of the population


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RUNNING GP


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FIVE MAJOR PREPARATORYSTEPS FOR GP

Determining the set of terminals

Determining the set of functions Determining the fitness measure Determining the parameters for the run Determining the method for designating a result

and the criterion for terminating a run


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GPdotNET Codeplex open source project Started with development in 2006, as PGS

First published on Codeplex at 5 Nov. 2009. WinForms, C#, .NET4.0, Mono2.8 This year will be released v2.0 Cross-OS and Cross Platform application .NET and Mono


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GPDOTNET USER PERSPECTIVE


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GPDOTNET DEV. PERSPECTIVE


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GPdotNET

Implementation Core Engine Util Common.Tools Application


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Chromosome

implementation- Tree based GP Chromosome

- Binary Type GA Chromosome- Continuous Type GA Chromosome

- Derived from IChromosome

- MemoryPool support at compile time


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Memory Pooling Chromosome Level Simple Stack implementation of

Pool Memory Pooling has to be Thread -

Safe


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DEMOMEMORY POOLINGIMPLEMENTATION


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Random Number

Generation Most important in this project Almost all data is generated randomly

Random has to be Thread-Safe ThreadLocal implementation


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DEMORANDOM IMPLEMENTATION


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Fitness level GP

paralelization


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Chromosome level ofParalelization


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Paralelization at level

of Independent runs


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DEMOPARALIZATION IN GPDOTNET


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More info

www.genetic-programming.org oficial web page http://gpdotnet.codeplex.com http://bhrnjica.wordpress.com/gpdotnet latest information

about the GPdotNET
http://www.genetic-programming.org/http://gpdotnet.codeplex.com/http://bhrnjica.wordpress.com/gpdotnethttp://bhrnjica.wordpress.com/gpdotnethttp://gpdotnet.codeplex.com/http://www.genetic-programming.org/http://www.genetic-programming.org/http://www.genetic-programming.org/

gpdotnetv2.0 - darwin's theory of evolution in solving engineering problems by c#

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