| /* |
| |
| 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 "TAOptimization.h" |
| #include "ProblemTest.h" |
| |
| |
| double TAOptimization::defaultAnnRate=0.4; |
| double TAOptimization::defaultMultiple=2.0; |
| |
| |
| TAOptimization::TAOptimization(Problem &p,double t,double d,int m) |
| : IterOptimization(p,m) , temperatur(t) , deltaTemperatur(d) |
| { |
| assert(t>0 && d>0); |
| } |
| |
| |
| |
| TAOptimization::TAOptimization(Problem&p,int m) |
| : IterOptimization(p,m), temperatur(-1) |
| { |
| } |
| |
| |
| |
| TAOptimization::TAOptimization(TAOptimization &o) |
| : IterOptimization(o) |
| { |
| temperatur= o.temperatur; |
| deltaTemperatur= o.deltaTemperatur; |
| } |
| |
| |
| |
| |
| void TAOptimization::zInitialize() |
| { |
| IterOptimization::zInitialize(); |
| if( temperatur<0) |
| { |
| |
| |
| int n; |
| |
| StatVar &v=problem.deviationStatVar(*this,ANZ_VERSCHLECHTERUNGEN); |
| |
| if(maxStep>0) |
| n=(int)(maxStep*4.0/5.0); |
| else |
| maxStep=n=(int)(problem.expectedNumberOfIterations()*defaultMultiple); |
| |
| temperatur = v.quantil(defaultAnnRate); |
| deltaTemperatur = temperatur/n; |
| |
| if( verboseMode>0 ) |
| cout << "#TA: (anfAnnRate=" |
| << defaultAnnRate << ",T=" << temperatur << ",deltaT=" |
| << deltaTemperatur << ")\n"; |
| curStep=0; |
| endFlag=0; |
| delete &v; |
| } |
| } |
| |
| |
| short TAOptimization::end() |
| { |
| |
| |
| if( temperatur>0 ) |
| { |
| endFlag=0; |
| bestStep=curStep; |
| } |
| return endFlag>0; |
| } |
| |
| short TAOptimization::accept(double delta) |
| { |
| if( temperatur<0 ) |
| return 1; |
| else |
| if( delta < temperatur ) |
| return 1; |
| else |
| return 0; |
| } |
| |
| void TAOptimization::abkuehlen() |
| { |
| if( temperatur>=0 ) |
| temperatur=(temperatur-deltaTemperatur>0)?(temperatur-deltaTemperatur):0; |
| } |
| |
| void TAOptimization::makeGraphOutput() |
| { |
| IterOptimization::makeGraphOutput(); |
| *GraphOutput << temperatur; |
| } |
| |
| |
| |
| |
| double TAOptimization::optimizeValue(Problem &p,int proParameter,int numParameter,int typ, |
| int optimierungsschritte,int print) |
| { |
| switch(typ) |
| { |
| case 1: |
| { |
| double bestPar=-1,best=1e100; |
| if(print)cout << "#TA-optimizeValues: " << numParameter << endl; |
| for(int i=0;i<=numParameter;i++) |
| { |
| StatVar end,laufzeit,init; |
| double now; |
| defaultAnnRate = (float)(i)/numParameter; |
| solveProblem(0,p,proParameter,optimierungsschritte,TA_OPT,now,end, |
| laufzeit,init); |
| if( best>now ) |
| { |
| best=now; |
| bestPar=defaultAnnRate; |
| } |
| if( print) |
| { |
| cout << defaultAnnRate << " "; |
| 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 << "#Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit Bester" |
| " Sigma SigmaSmaller SigmaBigger\n"; |
| defaultAnnRate=0.5; |
| return bestPar; |
| } |
| break; |
| case 10: |
| { |
| double bestPar=-1,best=1e100; |
| if( print ) |
| cout << "#TA-optimizeValues: defaultMultiple " << 10 << endl; |
| for(int i=1;i<=6;i++) |
| { |
| StatVar end,laufzeit,init; |
| double now; |
| defaultMultiple = i; |
| solveProblem(0,p,proParameter,optimierungsschritte,TA_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 << "#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 TAOptimization::optimizeValue (" |
| << typ << ")\n"; |
| exit(1); |
| } |
| return 1e100; |
| } |
| |
| |