From eb25bf0ab5dc35fbbe0270765d2b05b4d81531e1 Mon Sep 17 00:00:00 2001 From: evomarc Date: Fri, 4 May 2001 16:13:37 +0000 Subject: [PATCH] Removing old trash! --- eo/tutorial/html/FirstRealGA_old.html | 278 -------------------------- 1 file changed, 278 deletions(-) delete mode 100644 eo/tutorial/html/FirstRealGA_old.html diff --git a/eo/tutorial/html/FirstRealGA_old.html b/eo/tutorial/html/FirstRealGA_old.html deleted file mode 100644 index a634f529..00000000 --- a/eo/tutorial/html/FirstRealGA_old.html +++ /dev/null @@ -1,278 +0,0 @@ - - - - - - First Real GA - - -Back to Lesson 1 - Tutorial -main page - Algorithm-Based - Component-Based -page - Programming hints - EO -documentation -
-
-
-

-A First Real GA

-Click on the figure to see the corresponding code. Tutorial comments are -in variable length fonts, after the code. -
-

- -

//----------------------------------------------------------------------------- -

#include -<stdexcept > // runtime_error -

//----------------------------------------------------------------------------- -
// FirstRealGA.cpp -
//----------------------------------------------------------------------------- -
//* -
// An instance of a -VERY simple Real-coded Genetic Algorithm -
// -
//----------------------------------------------------------------------------- -
// standard includes -

#include -<iostream>// cout -
#include -<strstream>// ostrstream, istrstream -

// the general include -for eo -

#include -<eo> -

// specific incluse, -as Real is not (yet) in the standard eo source dir -
#include -"eoeal.h" -
#include -"eoRealOp.h" -

//----------------------------------------------------------------------------- -
// define your individual: -

typedef -eoReal<double> Indi; -

You say here that you will be handling arrays -of doubles, whose fitness is a double -
Note that this makes Indi derive from STL -class vector<double> -
//----------------------------------------------------------------------------- -
/** a simple fitness -function that computes the euclidian norm of a real vector -
    @param -_indi A real-valued individual -
*/ -

double -real_value(const Indi & _indi) -
{ -
  -double sum = 0; -
  -for (unsigned i = 0; i < _indi.size(); i++) -
      -sum += _indi[i]*_indi[i]; -
  -return (-sum);   // maximizing -
} -

This simple function computes the sum of the squares of the variables -(remember Indi is here a vector of doubles) -
//----------------------------------------------------------------------------- -

void -main_function(int argc, char **argv) -
{ -
const -unsigned int SEED = 42;// seed for random number generator -
const -unsigned int VEC_SIZE = 8; // Number of object variables in genotypes -
const -unsigned int POP_SIZE = 20; // Size of population -
const -unsigned int T_SIZE = 3; // size for tournament selection -
const -unsigned int MAX_GEN = 500; // Maximum number of generation before STOP -
const -float CROSS_RATE = 0.8; // Crossover rate -
const -double EPSILON = 0.01; // range for real uniform mutation -
const -float MUT_RATE = 0.5; // mutation rate -
  -

////////////////////////// -
// Random seed -
////////////////////////// -
//reproducible random -seed: if you don't change SEED above, -
// you'll aways get -the same result, NOT a random run -
rng.reseed(SEED); -

///////////////////////////// -
// Fitness function -
//////////////////////////// -
// Evaluation: from -a plain C++ fn to an EvalFunc Object -
eoEvalFuncPtr<Indi> -eval( real_value ); -

This encapsulate the C++ function real_value into a functor -object -

//////////////////////////////// -
// Initilisation of -population -
//////////////////////////////// -

// declare the population -
eoPop<Indi> -pop; -

Declares a population -object, which is basically an STL -vector<Indi> -

// fill it! -
for -(unsigned int igeno=0; igeno<POP_SIZE; igeno++) -
  -{ -
    -Indi v; // generate a random individual -
    -for (unsigned ivar=0; ivar<VEC_SIZE; ivar++) -
      -{ -
        -double r = 2*rng.uniform() - 1; // new value, random in [-1,1) -
        -v.push_back(r); // -
      -} -
    -eval(v); // evaluate it -
    -pop.push_back(v); // and put it in the population -
  -} -

This initialization of the population is straightforward -
rng.uniform() generates a double uniformly -in [0,1), -
v.push_back simply appends its argument -at the end of STL vector v -
eval(v)evaluates individal v -the functor way, calling eval.operator()(v) -

// sort pop before printing -it! -
pop.sort(); -

// Print (sorted) intial -population (raw printout) -
cout -<< "Initial Population" << endl; -
cout -<< pop; -

If you looked at eoPop -inheritance diagram, you noticed that it derives from eoPrintable: -hence you can stream them using the << operator. Of course, Indis -are EO objects -, which also are eoPrintable, and the << operator for eoPop -uses the << operator for Indi. -

///////////////////////////////////// -
// -selection and replacement -
//////////////////////////////////// -
// The well-known roulette -selection -
// -The robust tournament selection -
eoDetTournament<Indi> -select(T_SIZE); // SIZE in [2,POP_SIZE] -

// -eoSGA uses generational replacement by default -
// so no replacement -procedure has to be given -

////////////////////////////////////// -
// termination condition -
///////////////////////////////////// -
// stop after MAX_GEN -generations -
eoGenContinue<Indi> -continuator(MAX_GEN); -

This class is called eoGenContinue -because the main loop of all eoAlgo -says ... while continuator(pop) -

////////////////////////////////////// -
// -The variation operators -
////////////////////////////////////// -

// -offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon] -
eoUniformMutation<Indi>  -mutation(EPSILON); -
// -offspring(i) is a linear combination of parent(i) -
eoArithmeticCrossover<Indi> -xover; -

The variation operators are respectively -an eoMonOp -(unary operator) and an eoQuadOp -(binary operator that modifies both its arguments). -

///////////////////////////////////////// -
// the algorithm -
//////////////////////////////////////// -
// standard Generational -GA requires -
// selection, evaluation, -crossover and mutation, stopping criterion -
  -

eoSGA<Indi> -gga(select, xover, CROSS_RATE, mutation, MUT_RATE, -
eval, -continuator); -

// Apply algo to pop -- that's it! -
gga(pop); -

This simple algorithm of class eoSGA is a functor -object, and running the algorithm amounts to call the operator() -on the initial population! -

// Print (sorted) intial -population (raw printout) -
pop.sort(); -
cout -<< "FINAL Population\n" << pop << endl; -

that's it - just print the final population and you're done!!! -

} -

// -A main that catches the exceptions - do not modify! -
int -main(int argc, char **argv) -
{ -
#ifdef -_MSC_VER -
// -rng.reseed(42); -
int -flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF); -
flag -|= _CRTDBG_LEAK_CHECK_DF; -
_CrtSetDbgFlag(flag); -
// -_CrtSetBreakAlloc(100); -
#endif -

try -
{ -
main_function(argc, -argv); -
} -
catch(exception& -e) -
{ -
cout -<< "Exception: " << e.what() << '\n'; -
} -

return -1; -
} -

-

Back to Lesson 1 - Tutorial -main page - Algorithm-Based - Component-Based -page - Programming hints - EO -documentation -
-
-Marc Schoenauer
- -
Last -modified: Wed Nov 6 17:22:43 CET 2000 - -