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In the TSP, the fitness has to be minimized ... with all the needed modification (for example, moSA.h)

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@587 331e1502-861f-0410-8da2-ba01fb791d7f
This commit is contained in:
jboisson 2007-08-03 14:28:06 +00:00
commit 1d94071693
170 changed files with 748 additions and 837 deletions
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6
trunk/paradiseo-mo/src/moBestImprSelect.h
View file

@ -46,16 +46,13 @@ public:
*/
bool update (const M & __move, const Fitness & __fit)
{
if (first_time || __fit > best_fit)
if ((first_time) || (__fit > best_fit))
{
best_fit = __fit;
best_move = __move;
first_time = false;
}
return true;
}
@ -87,7 +84,6 @@ private:
//! The best fitness.
Fitness best_fit;
};
#endif

2
trunk/paradiseo-mo/src/moExponentialCoolingSchedule.h
View file

@ -23,7 +23,7 @@ class moExponentialCoolingSchedule: public moCoolingSchedule
{
public:
//! Simple constructor
//! Basic constructor
/*!
\param __threshold the threshold.
\param __ratio the ratio used to descrease the temperature.

16
trunk/paradiseo-mo/src/moFitSolContinue.h
View file

@ -29,9 +29,8 @@ public:
//! Basic constructor.
/*!
\param __fitness The fitness to reach.
\param __minimization Indicate if the the aim is to maximize or minimize the fitness.
*/
moFitSolContinue (Fitness __fitness, bool __minimization=true): fitness (__fitness), minimization(__minimization)
moFitSolContinue (Fitness __fitness): fitness (__fitness)
{}
//! Function that activates the stopping criterion.
@ -48,11 +47,7 @@ public:
return true;
}
if(minimization)
{
return __sol.fitness()>fitness;
}
return __sol.fitness()<=fitness;
return __sol.fitness() < fitness;
}
//! Procedure which allows to initialise all the stuff needed.
@ -63,13 +58,6 @@ private:
//! Fitness target.
Fitness fitness;
//! Flag that indicate if there is a minimization (true) or a maximization (false) of the fitness value.
/*!
It can be interesting to know this information because some solution-based metaheuristics can generate solution with a fitness that
is worse that the best known fitness (in this case, the counter is not reinitialized).
*/
bool minimization;
};
#endif

7
trunk/paradiseo-mo/src/moGenSolContinue.h
View file

@ -45,8 +45,13 @@ public:
}
//! Procedure which allows to initialise all the stuff needed.
/*!
It can be also used to reinitialize the counter all the needed things.
*/
void init ()
{}
{
numGen=0;
}
private:

38
trunk/paradiseo-mo/src/moHCMoveLoopExpl.h
View file

@ -64,31 +64,31 @@ moHCMoveLoopExpl (moMoveInit < M > &__move_init, moNextMove < M > &__next_move,
//
move_init (move, __old_sol); /* Restarting the exploration of
of the neighborhood ! */
move_select.init (__old_sol.fitness ());
while (move_select.update (move, incr_eval (move, __old_sol))
&& next_move (move, __old_sol));
try
{
M best_move;
Fitness best_move_fit;
move_select (best_move, best_move_fit);
__new_sol.fitness (best_move_fit);
best_move (__new_sol);
}
{
M best_move;
Fitness best_move_fit;
move_select (best_move, best_move_fit);
__new_sol.fitness (best_move_fit);
best_move (__new_sol);
}
catch (EmptySelection & __ex)
{
// ?
}
{
// ?
}
}
private:
//! Move initialiser.

24
trunk/paradiseo-mo/src/moNoFitImprSolContinue.h
View file

@ -29,11 +29,9 @@ public:
//! Basic constructor.
/*!
\param __maxNumberOfIterationWithoutImprovement The number of iterations without fitness improvement to reach for stop.
\param __minimization Indicate if the the aim is to maximize or minimize the fitness.
*/
moNoFitImprSolContinue (unsigned int __maxNumberOfIterationWithoutImprovement, bool __minimization=true)
: maxNumberOfIterationsWithoutImprovement(__maxNumberOfIterationWithoutImprovement),minimization(__minimization),
firstFitnessSaved(true), counter(0)
moNoFitImprSolContinue (unsigned int __maxNumberOfIterationWithoutImprovement)
: maxNumberOfIterationsWithoutImprovement(__maxNumberOfIterationWithoutImprovement), firstFitnessSaved(true), counter(0)
{}
//! Function that activates the stopping criterion.
@ -59,8 +57,7 @@ public:
counter++;
if( ((minimization) && (__sol.fitness() < fitness)) ||
((!minimization) && (__sol.fitness() > fitness)) )
if( __sol.fitness() > fitness)
{
fitness=__sol.fitness();
counter=0;
@ -74,8 +71,14 @@ public:
}
//! Procedure which allows to initialise all the stuff needed.
/*!
It can be also used to reinitialize the counter all the needed things.
*/
void init ()
{}
{
firstFitnessSaved=true;
counter=0;
}
private:
@ -88,13 +91,6 @@ private:
//! Current Fitness.
Fitness fitness;
//! Flag that indicate if there is a minimization (true) or a maximization (false) of the fitness value.
/*!
It can be interesting to know this information because some solution-based metaheuristics can generate solutions wiht a fitness that
is worse that the best known fitness (in this case, the counter is not reinitialized).
*/
bool minimization;
//! The iteration couter.
unsigned int counter;
};

42
trunk/paradiseo-mo/src/moSA.h
View file

@ -31,16 +31,10 @@ template < class M > class moSA:public moAlgo < typename M::EOType >
{
//! Alias for the type
typedef
typename
M::EOType
EOT;
typedef typename M::EOType EOT;
//! Alias for the fitness
typedef
typename
EOT::Fitness
Fitness;
typedef typename EOT::Fitness Fitness;
public:
@ -91,32 +85,38 @@ public:
EOT best_sol = __sol;
Fitness current_fitness, delta;
double exp1, exp2;
do
{
cont.init ();
do
{
move_rand (move);
Fitness delta_fit = incr_eval (move, __sol) - __sol.fitness ();
current_fitness= incr_eval (move, __sol);
if (delta_fit > 0 || rng.uniform () < exp (delta_fit / temp))
delta = current_fitness - __sol.fitness();
if(((long double)delta) < 0.0)
{
__sol.fitness (incr_eval (move, __sol));
move (__sol);
/* Updating the best solution found
until now ? */
if (__sol.fitness () > best_sol.fitness ())
best_sol = __sol;
delta=-delta;
}
if ((current_fitness > __sol.fitness()) || ((rng.uniform ()) < (exp (-delta/ temp))))
{
__sol.fitness (current_fitness);
move (__sol);
/* Updating the best solution found until now ? */
if (__sol.fitness () > best_sol.fitness ())
{
best_sol = __sol;
}
}
}
while (cont (__sol));
}
while (cool_sched (temp));

24
trunk/paradiseo-mo/src/moSteadyFitSolContinue.h
View file

@ -30,11 +30,10 @@ public:
/*!
\param __maxNumberOfIterations The number of iterations to reach before looking for the fitness.
\param __maxNumberOfIterationWithoutImprovement The number of iterations without fitness improvement to reach for stop.
\param __minimization Indicate if the the aim is to maximize or minimize the fitness.
*/
moSteadyFitSolContinue (unsigned int __maxNumberOfIterations, unsigned int __maxNumberOfIterationWithoutImprovement, bool __minimization=true)
moSteadyFitSolContinue (unsigned int __maxNumberOfIterations, unsigned int __maxNumberOfIterationWithoutImprovement)
: maxNumberOfIterations (__maxNumberOfIterations), maxNumberOfIterationsWithoutImprovement(__maxNumberOfIterationWithoutImprovement),
minimization(__minimization), maxNumberOfIterationsReached(false), firstFitnessSaved(true), counter(0)
maxNumberOfIterationsReached(false), firstFitnessSaved(true), counter(0)
{}
//! Function that activates the stopping criterion.
@ -71,8 +70,7 @@ public:
counter++;
if( ((minimization) && (__sol.fitness() < fitness)) ||
((!minimization) && (__sol.fitness() > fitness)) )
if( __sol.fitness() > fitness )
{
fitness=__sol.fitness();
counter=0;
@ -86,8 +84,15 @@ public:
}
//! Procedure which allows to initialise the stuff needed.
/*!
It can be also used to reinitialize the counter all the needed things.
*/
void init ()
{}
{
maxNumberOfIterationsReached=false;
counter=0;
firstFitnessSaved=true;
}
private:
@ -106,13 +111,6 @@ private:
//! Current Fitness.
Fitness fitness;
//! Flag that indicate if there is a minimization (true) or a maximization (false) of the fitness value.
/*!
It can be interesting to know this information because some solution-based metaheuristics can generate solution with a fitness that
is worse that the best known fitness (in this case, the counter is not reinitialized).
*/
bool minimization;
//! The iteration couter.
unsigned int counter;
};

7
trunk/paradiseo-mo/src/moTS.h
View file

@ -91,13 +91,13 @@ moTS (moMoveExpl < M > &__move_expl, moSolContinue < EOT > &__cont, eoEvalFunc <
M move;
EOT best_sol = __sol, new_sol;
EOT best_sol, new_sol;
best_sol = __sol;
cont.init ();
do
{
new_sol = __sol;
try
@ -112,8 +112,7 @@ moTS (moMoveExpl < M > &__move_expl, moSolContinue < EOT > &__cont, eoEvalFunc <
break;
}
/* Updating the best solution
found until now ? */
/* Updating the best solution found until now ? */
if (new_sol.fitness () > __sol.fitness ())
{
best_sol = new_sol;