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diff --git a/mgizapp/src/mkcls/SAOptimization.cpp b/mgizapp/src/mkcls/SAOptimization.cpp
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-/*
-
-Copyright (C) 1997,1998,1999,2000,2001 Franz Josef Och
-
-mkcls - a program for making word classes .
-
-This program is free software; you can redistribute it and/or
-modify it under the terms of the GNU General Public License
-as published by the Free Software Foundation; either version 2
-of the License, or (at your option) any later version.
-
-This program is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with this program; if not, write to the Free Software
-Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307,
-USA.
-
-*/
-
-
-
-
-#include <stdlib.h>
-#include <iostream>
-
-#include "SAOptimization.h"
-
-#include "ProblemTest.h"
-
-#define ALPHA 0.95
-
-double SAOptimization::defaultAnfAnnRate=0.9;
-double SAOptimization::defaultEndAnnRate=1e-9;
-double SAOptimization::defaultMultiple=2.0;
-
-
-
-SAOptimization::SAOptimization(Problem &p,int m)
-: IterOptimization(p,m), temperatur(-1)
-{
-}
-
-
-
-
-SAOptimization::SAOptimization(Problem &p,double t,double a,int s,int m)
-: IterOptimization(p,m),temperatur(t), alpha(a),schrittzahl(s)
-{
- assert(alpha<1);
- assert(schrittzahl>0);
- assert(t>0);
-}
-
-
-SAOptimization::SAOptimization(SAOptimization &o)
-: IterOptimization(o)
-{
- temperatur = o.temperatur;
- endTemperatur = o.endTemperatur;
- alpha = o.alpha;
- schrittzahl = o.schrittzahl;
- stepsForAbkuehlung = o.stepsForAbkuehlung;
-}
-
-
-void SAOptimization::zInitialize()
-{
- IterOptimization::zInitialize();
- if( temperatur<0)
- {
-
-
-
- StatVar &v=problem.deviationStatVar(*this,ANZ_VERSCHLECHTERUNGEN);
-
- if( maxStep>0 )
- stepsForAbkuehlung=(int)(maxStep*4.0/5.0);
- else
- maxStep=stepsForAbkuehlung=(int)(problem.expectedNumberOfIterations()*
- defaultMultiple);
-
- temperatur = v.getMean()/log(1/defaultAnfAnnRate);
- endTemperatur = v.getMean()/log(1/defaultEndAnnRate);
- schrittzahl = (int)(stepsForAbkuehlung/(log(endTemperatur/temperatur)/
- log(ALPHA)));
- if(schrittzahl==0)schrittzahl=1;
- alpha = ALPHA;
-
- if( verboseMode )
- cout << "#Algorithm: Simulated Annealing(anfAnnRate="
- << defaultAnfAnnRate <<",(endAnnRate=" << defaultEndAnnRate
- << ",T0=" << temperatur<< ",Te=" << endTemperatur<< ",schrittzahl="
- << schrittzahl<< ",stepsForAbkuehlung=" << stepsForAbkuehlung
- << ")\n";
- curStep=0;
- endFlag=0;
- delete &v;
- problem.initialize();
- IterOptimization::zInitialize();
- }
-}
-
-short SAOptimization::end()
-{
- if( temperatur>endTemperatur )
- bestStep = curStep;
- if( endFlag>0 && temperatur<endTemperatur)
- return 1;
- else
- return 0;
-}
-void SAOptimization::abkuehlen()
-{
- if(temperatur>=0)
- {
- if( curStep%schrittzahl == 0 )
- temperatur=temperatur * alpha;
- if( curStep> stepsForAbkuehlung)
- temperatur = 0;
- }
-}
-short SAOptimization::accept(double delta)
-{
- if( temperatur<0 )
- return 1;
- else
- {
- if( delta > 0 )
- {
- if( temperatur==0 )
- return 0;
- else
- {
- double z=zufall01();
- assert(z!=0.0);
- if(z==0.0)
- z+=1e-20;
- double e=exp(-delta/temperatur);
-
-
-
- return z+0.000000000001<=e;
- }
- }
- else
- return 1;
- }
-}
-
-void SAOptimization::makeGraphOutput()
-{
- IterOptimization::makeGraphOutput();
- *GraphOutput << temperatur;
-}
-
-
-
-
-double SAOptimization::optimizeValue(Problem &p,int proParameter,int numParameter,
- int typ,int optimierungsschritte,int print)
-{
- switch(typ)
- {
- case 1:
- {
- double bestPar=-1,best=1e100;
- double now;
- if( print )
- cout << "#SA-optimizeValues: defaultAnfAnnRate" << endl;
- for(int i=0;i<numParameter;i++)
- {
- StatVar end,laufzeit,init;
- defaultAnfAnnRate=0.1 + (1.0/numParameter)*i;
- solveProblem(0,p,proParameter,optimierungsschritte,SA_OPT,now,
- end,laufzeit,init);
- if( best>now )
- {
- best=now;
- bestPar=defaultAnfAnnRate;
- }
- if( print )
- {
- cout << defaultAnfAnnRate << " ";
- cout << end.getMean() << " " << end.quantil(0.2) << " "
- << end.quantil(0.79) << " " << laufzeit.getMean() << " "
- << end.quantil(0.0) << " " << end.getSigma() << " "
- << end.getSigmaSmaller() << " " << end.getSigmaBigger()
- << " " << now << endl;
- }
- }
- if( print )
- cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit "
- "Bester Sigma SigmaSmaller SigmaBigger\n";
- defaultAnfAnnRate=0.9;
- return bestPar;
- }
- break;
- case 2:
- {
- double bestPar=-1,best=1e100;
- double now;
- if( print )
- cout << "#Optimierung von SA: defaultEndAnnRate" << endl;
- for(int i=1;i<=numParameter;i++)
- {
- StatVar end,laufzeit,init;
- defaultEndAnnRate=1/(pow(10.0,i));
- solveProblem(0,p,proParameter,optimierungsschritte,SA_OPT,now,end,
- laufzeit,init);
- if( best>now )
- {
- best=now;
- bestPar=defaultEndAnnRate;
- }
- if( print )
- {
- cout << defaultEndAnnRate << " ";
- cout << end.getMean() << " " << end.quantil(0.2) << " "
- << end.quantil(0.79) << " " << laufzeit.getMean() << " "
- << end.quantil(0.0) << " " << end.getSigma() << " "
- << end.getSigmaSmaller() << " " << end.getSigmaBigger()
- << " " << now << endl;
- }
- }
- if( print )
- cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit "
- "Bester Sigma SigmaSmaller SigmaBigger\n";
- defaultEndAnnRate=1/10000.0;
- return bestPar;
- }
- break;
- case 10:
- {
- double bestPar=-1,best=1e100;
-
- if( print )
- cout << "#SA-optimizeValues: defaultMultiple " << 8 << endl;
- for(int i=1;i<=6;i++)
- {
- StatVar end,laufzeit,init;
- double now;
- defaultMultiple = i;
- solveProblem(0,p,proParameter,optimierungsschritte,SA_OPT,now,end,
- laufzeit,init);
- if( best>now )
- {
- best=now;
- bestPar=defaultMultiple;
- }
- if( print )
- {
- cout << defaultMultiple << " ";
- cout << end.getMean() << " " << end.quantil(0.2) << " "
- << end.quantil(0.79) << " " << laufzeit.getMean() << " "
- << end.quantil(0.0) << " " << end.getSigma() << " "
- << end.getSigmaSmaller() << " " << end.getSigmaBigger()
- << " " << now << endl;
- }
- }
- if( print )
- cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit "
- "Bester Sigma SigmaSmaller SigmaBigger\n";
- defaultMultiple=2.0;
- return bestPar;
- }
- break;
- default:
- cerr << "Error: wrong parameter-type in SAOptimization::optimizeValue ("
- << typ << ")\n";
- exit(1);
- }
- return 1e100;
-}
-
-
-
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