| /* |
| |
| 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 "RRTOptimization.h" |
| #include "ProblemTest.h" |
| |
| double RRTOptimization::defaultAnnRate=0.6; |
| double RRTOptimization::defaultMultiple=2.0; |
| |
| |
| |
| RRTOptimization::RRTOptimization(Problem &p,double t,double dt,int m) |
| : IterOptimization(p,m),deviation(t),deltaDeviation(dt) |
| { |
| assert(deviation>=0); |
| } |
| |
| |
| |
| RRTOptimization:: RRTOptimization(Problem &p,int m) |
| : IterOptimization(p,m),deviation(-1),deltaDeviation(0) |
| { |
| } |
| |
| |
| |
| RRTOptimization::RRTOptimization(RRTOptimization &o) |
| : IterOptimization(o) |
| { |
| deviation = o.deviation; |
| deltaDeviation= o.deltaDeviation; |
| record = o.record; |
| } |
| |
| |
| |
| void RRTOptimization::zInitialize() |
| { |
| IterOptimization::zInitialize(); |
| if( deviation<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); |
| |
| deviation = v.quantil(defaultAnnRate); |
| deltaDeviation = deviation/(float)n; |
| |
| if( verboseMode>0 ) |
| cout << "#Algorithm: Record-To-Record-Travel: (anfAnnRate=" |
| << defaultAnnRate << ",T=" << deviation << ",deltaT=" |
| << deltaDeviation << ")\n"; |
| |
| curStep=0; |
| endFlag=0; |
| delete &v; |
| problem.initialize(); |
| IterOptimization::zInitialize(); |
| } |
| record=problem.value(); |
| assert(deviation>=0); |
| } |
| |
| short RRTOptimization::end() |
| { |
| return ( endFlag>0 && deviation==0.0 ); |
| } |
| void RRTOptimization::abkuehlen() |
| { |
| if( deviation>=0 ) |
| { |
| deviation -= deltaDeviation; |
| if(deviation<0) |
| deviation=0; |
| } |
| } |
| short RRTOptimization::accept(double delta) |
| { |
| if( deviation<0 ) |
| return 1; |
| else |
| { |
| if( delta + curValue - deviation < record ) |
| { |
| if( delta + curValue < record ) |
| record = delta+curValue; |
| return 1; |
| } |
| else |
| return 0; |
| } |
| } |
| |
| void RRTOptimization::makeGraphOutput() |
| { |
| IterOptimization::makeGraphOutput(); |
| *GraphOutput << deviation; |
| } |
| |
| |
| |
| |
| double RRTOptimization::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 << "#RRT-optimizeValues: Quantil: " << numParameter << endl; |
| for(int i=0;i<=numParameter;i++) |
| { |
| StatVar end,laufzeit,init; |
| double now; |
| if(i==0) defaultAnnRate=0.2; |
| else defaultAnnRate = 0.3+(float)(0.6*i)/numParameter; |
| solveProblem(0,p,proParameter,optimierungsschritte,RRT_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 << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit " |
| "Bester Sigma SigmaSmaller SigmaBigger\n"; |
| defaultAnnRate=0.8; |
| return bestPar; |
| } |
| break; |
| case 10: |
| { |
| double i; |
| double bestPar=-1,best=1e100; |
| StatVar end,laufzeit,init; |
| |
| if( print ) |
| cout << "#RRT-optimizeValues: defaultMultiple" << 8 << endl; |
| for(i=0.5;i<=10;i+=1.5) |
| { |
| double now; |
| defaultMultiple = i; |
| solveProblem(0,p,proParameter,optimierungsschritte,RRT_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 RRTOptimization::optimizeValue (" |
| << typ << ")\n"; |
| exit(1); |
| } |
| return 1e100; |
| } |
| |
| |