STD.tpl 17.6 KB
Newer Older
kruger's avatar
kruger committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
\TEMPLATE_START
#ifdef WIN32
#define _CRT_SECURE_NO_WARNINGS
#pragma comment(lib, "libEasea.lib")
#pragma comment(lib, "Winmm.lib")
#endif
/**
 This is program entry for STD template for EASEA

*/

\ANALYSE_PARAMETERS
#include <stdlib.h>
#include <iostream>
#include <time.h>
#include "COptionParser.h"
#include "CRandomGenerator.h"
#include "CEvolutionaryAlgorithm.h"
#include "global.h"
#include "EASEAIndividual.hpp"

using namespace std;

/** Global variables for the whole algorithm */
CIndividual** pPopulation = NULL;
CIndividual*  bBest = NULL;
float* pEZ_MUT_PROB = NULL;
float* pEZ_XOVER_PROB = NULL;
size_t *EZ_NB_GEN;
size_t *EZ_current_generation;
CEvolutionaryAlgorithm* EA;

int main(int argc, char** argv){


	parseArguments("EASEA.prm",argc,argv);

	ParametersImpl p;
	p.setDefaultParameters(argc,argv);
	CEvolutionaryAlgorithm* ea = p.newEvolutionaryAlgorithm();

	EA = ea;

	EASEAInit(argc,argv);

	CPopulation* pop = ea->getPopulation();

	ea->runEvolutionaryLoop();

	EASEAFinal(pop);

	delete pop;


#ifdef WIN32
	system("pause");
#endif
	return 0;
}

\START_CUDA_GENOME_CU_TPL
#ifdef WIN32
#define _CRT_SECURE_NO_WARNINGS
#pragma comment(lib, "libEasea.lib")
#endif

#include <fstream>
#ifndef WIN32
#include <sys/time.h>
#else
#include <time.h>
#endif
#include <string>
#include <sstream>
#include "CRandomGenerator.h"
#include "CPopulation.h"
#include "COptionParser.h"
#include "CStoppingCriterion.h"
#include "CEvolutionaryAlgorithm.h"
#include "global.h"
#include "CIndividual.h"

using namespace std;

#include "EASEAIndividual.hpp"
bool INSTEAD_EVAL_STEP = false;

CRandomGenerator* globalRandomGenerator;
extern CEvolutionaryAlgorithm* EA;
#define STD_TPL

\INSERT_USER_DECLARATIONS
\ANALYSE_USER_CLASSES

\INSERT_USER_CLASSES

\INSERT_USER_FUNCTIONS

\INSERT_INITIALISATION_FUNCTION
\INSERT_FINALIZATION_FUNCTION

\INSERT_BOUND_CHECKING

void evale_pop_chunk(CIndividual** population, int popSize){
  \INSTEAD_EVAL_FUNCTION
}

void EASEAInit(int argc, char** argv){
	\INSERT_INIT_FCT_CALL
}

void EASEAFinal(CPopulation* pop){
	\INSERT_FINALIZATION_FCT_CALL;
}

void AESAEBeginningGenerationFunction(CEvolutionaryAlgorithm* evolutionaryAlgorithm){
	\INSERT_BEGIN_GENERATION_FUNCTION
}

void AESAEEndGenerationFunction(CEvolutionaryAlgorithm* evolutionaryAlgorithm){
	\INSERT_END_GENERATION_FUNCTION
}

void AESAEGenerationFunctionBeforeReplacement(CEvolutionaryAlgorithm* evolutionaryAlgorithm){
	\INSERT_GENERATION_FUNCTION_BEFORE_REPLACEMENT
}


IndividualImpl::IndividualImpl() : CIndividual() {
  \GENOME_CTOR 
  \INSERT_EO_INITIALISER
  valid = false;
}

CIndividual* IndividualImpl::clone(){
	return new IndividualImpl(*this);
}

IndividualImpl::~IndividualImpl(){
  \GENOME_DTOR
}


float IndividualImpl::evaluate(){
  if(valid)
    return fitness;
  else{
    valid = true;
    \INSERT_EVALUATOR
  }
}

string IndividualImpl::serialize(){
    ostringstream AESAE_Line(ios_base::app);
    \GENOME_SERIAL
156
    AESAE_Line << this->fitness;
kruger's avatar
kruger committed
157
158
159
160
161
162
163
    return AESAE_Line.str();
}

void IndividualImpl::deserialize(string Line){
    istringstream AESAE_Line(Line);
    string line;
    \GENOME_DESERIAL
164
165
    AESAE_Line >> this->fitness;
    this->valid=true;
kruger's avatar
kruger committed
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
}

IndividualImpl::IndividualImpl(const IndividualImpl& genome){

  // ********************
  // Problem specific part
  \COPY_CTOR


  // ********************
  // Generic part
  this->valid = genome.valid;
  this->fitness = genome.fitness;
}


CIndividual* IndividualImpl::crossover(CIndividual** ps){
	// ********************
	// Generic part
	IndividualImpl** tmp = (IndividualImpl**)ps;
	IndividualImpl parent1(*this);
	IndividualImpl parent2(*tmp[0]);
	IndividualImpl child(*this);

	//DEBUG_PRT("Xover");
	/*   cout << "p1 : " << parent1 << endl; */
	/*   cout << "p2 : " << parent2 << endl; */

	// ********************
	// Problem specific part
  	\INSERT_CROSSOVER


	child.valid = false;
	/*   cout << "child : " << child << endl; */
	return new IndividualImpl(child);
}


void IndividualImpl::printOn(std::ostream& os) const{
	\INSERT_DISPLAY
}

std::ostream& operator << (std::ostream& O, const IndividualImpl& B)
{
  // ********************
  // Problem specific part
  O << "\nIndividualImpl : "<< std::endl;
  O << "\t\t\t";
  B.printOn(O);

  if( B.valid ) O << "\t\t\tfitness : " << B.fitness;
  else O << "fitness is not yet computed" << std::endl;
  return O;
}


size_t IndividualImpl::mutate( float pMutationPerGene ){
  this->valid=false;


  // ********************
  // Problem specific part
  \INSERT_MUTATOR
}

void ParametersImpl::setDefaultParameters(int argc, char** argv){

	this->minimizing = \MINIMAXI;
	this->nbGen = setVariable("nbGen",(int)\NB_GEN);
236
237
238
239
240

	seed = setVariable("seed",(int)time(0));
	globalRandomGenerator = new CRandomGenerator(seed);
	this->randomGenerator = globalRandomGenerator;

kruger's avatar
kruger committed
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316

	selectionOperator = getSelectionOperator(setVariable("selectionOperator","\SELECTOR_OPERATOR"), this->minimizing, globalRandomGenerator);
	replacementOperator = getSelectionOperator(setVariable("reduceFinalOperator","\RED_FINAL_OPERATOR"),this->minimizing, globalRandomGenerator);
	parentReductionOperator = getSelectionOperator(setVariable("reduceParentsOperator","\RED_PAR_OPERATOR"),this->minimizing, globalRandomGenerator);
	offspringReductionOperator = getSelectionOperator(setVariable("reduceOffspringOperator","\RED_OFF_OPERATOR"),this->minimizing, globalRandomGenerator);
	selectionPressure = setVariable("selectionPressure",(float)\SELECT_PRM);
	replacementPressure = setVariable("reduceFinalPressure",(float)\RED_FINAL_PRM);
	parentReductionPressure = setVariable("reduceParentsPressure",(float)\RED_PAR_PRM);
	offspringReductionPressure = setVariable("reduceOffspringPressure",(float)\RED_OFF_PRM);
	pCrossover = \XOVER_PROB;
	pMutation = \MUT_PROB;
	pMutationPerGene = 0.05;

	parentPopulationSize = setVariable("popSize",(int)\POP_SIZE);
	offspringPopulationSize = setVariable("nbOffspring",(int)\OFF_SIZE);


	parentReductionSize = setReductionSizes(parentPopulationSize, setVariable("survivingParents",(float)\SURV_PAR_SIZE));
	offspringReductionSize = setReductionSizes(offspringPopulationSize, setVariable("survivingOffspring",(float)\SURV_OFF_SIZE));

	this->elitSize = setVariable("elite",(int)\ELITE_SIZE);
	this->strongElitism = setVariable("eliteType",(int)\ELITISM);

	if((this->parentReductionSize + this->offspringReductionSize) < this->parentPopulationSize){
		printf("*WARNING* parentReductionSize + offspringReductionSize < parentPopulationSize\n");
		printf("*WARNING* change Sizes in .prm or .ez\n");
		printf("EXITING\n");
		exit(1);	
	} 
	if((this->parentPopulationSize-this->parentReductionSize)>this->parentPopulationSize-this->elitSize){
		printf("*WARNING* parentPopulationSize - parentReductionSize > parentPopulationSize - elitSize\n");
		printf("*WARNING* change Sizes in .prm or .ez\n");
		printf("EXITING\n");
		exit(1);	
	} 
	if(!this->strongElitism && ((this->offspringPopulationSize - this->offspringReductionSize)>this->offspringPopulationSize-this->elitSize)){
		printf("*WARNING* offspringPopulationSize - offspringReductionSize > offspringPopulationSize - elitSize\n");
		printf("*WARNING* change Sizes in .prm or .ez\n");
		printf("EXITING\n");
		exit(1);	
	} 
	

	/*
	 * The reduction is set to true if reductionSize (parent or offspring) is set to a size less than the
	 * populationSize. The reduction size is set to populationSize by default
	 */
	if(offspringReductionSize<offspringPopulationSize) offspringReduction = true;
	else offspringReduction = false;

	if(parentReductionSize<parentPopulationSize) parentReduction = true;
	else parentReduction = false;

	cout << "Parent red " << parentReduction << " " << parentReductionSize << "/"<< parentPopulationSize << endl;
	cout << "Parent red " << offspringReduction << " " << offspringReductionSize << "/" << offspringPopulationSize << endl;

	generationalCriterion = new CGenerationalCriterion(setVariable("nbGen",(int)\NB_GEN));
	controlCStopingCriterion = new CControlCStopingCriterion();
	timeCriterion = new CTimeCriterion(setVariable("timeLimit",\TIME_LIMIT));

	this->optimise = 0;

	this->printStats = setVariable("printStats",\PRINT_STATS);
	this->generateCSVFile = setVariable("generateCSVFile",\GENERATE_CSV_FILE);
	this->generateGnuplotScript = setVariable("generateGnuplotScript",\GENERATE_GNUPLOT_SCRIPT);
	this->generateRScript = setVariable("generateRScript",\GENERATE_R_SCRIPT);
	this->plotStats = setVariable("plotStats",\PLOT_STATS);
	this->printInitialPopulation = setVariable("printInitialPopulation",0);
	this->printFinalPopulation = setVariable("printFinalPopulation",0);
	this->savePopulation = setVariable("savePopulation",\SAVE_POPULATION);
	this->startFromFile = setVariable("startFromFile",\START_FROM_FILE);

	this->outputFilename = (char*)"EASEA";
	this->plotOutputFilename = (char*)"EASEA.png";

	this->remoteIslandModel = setVariable("remoteIslandModel",\REMOTE_ISLAND_MODEL);
kruger's avatar
kruger committed
317
	this->ipFile = (char*)setVariable("ipFile","\IP_FILE").c_str();
kruger's avatar
kruger committed
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
}

CEvolutionaryAlgorithm* ParametersImpl::newEvolutionaryAlgorithm(){

	pEZ_MUT_PROB = &pMutationPerGene;
	pEZ_XOVER_PROB = &pCrossover;
	EZ_NB_GEN = (size_t*)setVariable("nbGen",\NB_GEN);
	EZ_current_generation=0;

	CEvolutionaryAlgorithm* ea = new EvolutionaryAlgorithmImpl(this);
	generationalCriterion->setCounterEa(ea->getCurrentGenerationPtr());
	ea->addStoppingCriterion(generationalCriterion);
	ea->addStoppingCriterion(controlCStopingCriterion);
	ea->addStoppingCriterion(timeCriterion);	

	EZ_NB_GEN=((CGenerationalCriterion*)ea->stoppingCriteria[0])->getGenerationalLimit();
	EZ_current_generation=&(ea->currentGeneration);

	 return ea;
}

void EvolutionaryAlgorithmImpl::initializeParentPopulation(){
	if(this->params->startFromFile){
	  ifstream AESAE_File("EASEA.pop");
	  string AESAE_Line;
  	  for( unsigned int i=0 ; i< this->params->parentPopulationSize ; i++){
	  	  getline(AESAE_File, AESAE_Line);
		  this->population->addIndividualParentPopulation(new IndividualImpl(),i);
		  ((IndividualImpl*)this->population->parents[i])->deserialize(AESAE_Line);
	  }
	  
349
	}
kruger's avatar
kruger committed
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
	else{
  	  for( unsigned int i=0 ; i< this->params->parentPopulationSize ; i++){
		  this->population->addIndividualParentPopulation(new IndividualImpl(),i);
	  }
	}
        this->population->actualParentPopulationSize = this->params->parentPopulationSize;
}


EvolutionaryAlgorithmImpl::EvolutionaryAlgorithmImpl(Parameters* params) : CEvolutionaryAlgorithm(params){
	;
}

EvolutionaryAlgorithmImpl::~EvolutionaryAlgorithmImpl(){

}

\START_CUDA_GENOME_H_TPL

#ifndef PROBLEM_DEP_H
#define PROBLEM_DEP_H

//#include "CRandomGenerator.h"
#include <stdlib.h>
#include <iostream>
#include <CIndividual.h>
#include <Parameters.h>
kruger's avatar
kruger committed
377
#include <string>
kruger's avatar
kruger committed
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449

using namespace std;

class CRandomGenerator;
class CSelectionOperator;
class CGenerationalCriterion;
class CEvolutionaryAlgorithm;
class CPopulation;
class Parameters;

\INSERT_USER_CLASSES_DEFINITIONS

class IndividualImpl : public CIndividual {

public: // in EASEA the genome is public (for user functions,...)
	// Class members
  	\INSERT_GENOME


public:
	IndividualImpl();
	IndividualImpl(const IndividualImpl& indiv);
	virtual ~IndividualImpl();
	float evaluate();
	static size_t getCrossoverArrity(){ return 2; }
	float getFitness(){ return this->fitness; }
	CIndividual* crossover(CIndividual** p2);
	void printOn(std::ostream& O) const;
	CIndividual* clone();

	size_t mutate(float pMutationPerGene);
	string serialize();
	void deserialize(string AESAE_Line);

	friend std::ostream& operator << (std::ostream& O, const IndividualImpl& B) ;
	void initRandomGenerator(CRandomGenerator* rg){ IndividualImpl::rg = rg;}

};


class ParametersImpl : public Parameters {
public:
	void setDefaultParameters(int argc, char** argv);
	CEvolutionaryAlgorithm* newEvolutionaryAlgorithm();
};

/**
 * @TODO ces functions devraient s'appeler weierstrassInit, weierstrassFinal etc... (en gros EASEAFinal dans le tpl).
 *
 */

void EASEAInit(int argc, char** argv);
void EASEAFinal(CPopulation* pop);
void EASEABeginningGenerationFunction(CEvolutionaryAlgorithm* evolutionaryAlgorithm);
void EASEAEndGenerationFunction(CEvolutionaryAlgorithm* evolutionaryAlgorithm);
void EASEAGenerationFunctionBeforeReplacement(CEvolutionaryAlgorithm* evolutionaryAlgorithm);


class EvolutionaryAlgorithmImpl: public CEvolutionaryAlgorithm {
public:
	EvolutionaryAlgorithmImpl(Parameters* params);
	virtual ~EvolutionaryAlgorithmImpl();
	void initializeParentPopulation();
};

#endif /* PROBLEM_DEP_H */

\START_CUDA_MAKEFILE_TPL


UNAME := $(shell uname)

Ogier Maitre's avatar
Ogier Maitre committed
450
EASEALIB_PATH=$(EZ_PATH)/libeasea/
kruger's avatar
kruger committed
451
452
453
454
455
456
457
458
459

CXXFLAGS =	-O2 -g -Wall -fmessage-length=0 -I$(EASEALIB_PATH)include -I$(EZ_PATH)boost

#USER MAKEFILE OPTIONS :
\INSERT_MAKEFILE_OPTION#END OF USER MAKEFILE OPTIONS


OBJS = EASEA.o EASEAIndividual.o 

Frédéric Krüger's avatar
Frédéric Krüger committed
460
LIBS = -lpthread 
kruger's avatar
kruger committed
461
462
463
464

TARGET =	EASEA

$(TARGET):	$(OBJS)
465
	$(CXX) -o $(TARGET) $(OBJS) $(LDFLAGS) $(LIBS) -g $(EASEALIB_PATH)/libeasea.a $(EZ_PATH)boost/program_options.a
kruger's avatar
kruger committed
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652

	
#%.o:%.cpp
#	$(CXX) -c $(CXXFLAGS) $^

all:	$(TARGET)
clean:
	rm -f $(OBJS) $(TARGET)
easeaclean:
	rm -f $(TARGET) *.o *.cpp *.hpp EASEA.png EASEA.dat EASEA.prm EASEA.mak Makefile EASEA.vcproj EASEA.csv EASEA.r EASEA.plot EASEA.pop
	
\START_VISUAL_TPL<?xml version="1.0" encoding="Windows-1252"?>
<VisualStudioProject
	ProjectType="Visual C++"
	Version="9,00"
	Name="EASEA"
	ProjectGUID="{E73D5A89-F262-4F0E-A876-3CF86175BC30}"
	RootNamespace="EASEA"
	Keyword="Win32Proj"
	TargetFrameworkVersion="196613"
	>
	<Platforms>
		<Platform
			Name="Win32"
		/>
	</Platforms>
	<ToolFiles>
	</ToolFiles>
	<Configurations>
		<Configuration
			Name="Release|Win32"
			OutputDirectory="$(SolutionDir)"
			IntermediateDirectory="$(ConfigurationName)"
			ConfigurationType="1"
			CharacterSet="1"
			WholeProgramOptimization="1"
			>
			<Tool
				Name="VCPreBuildEventTool"
			/>
			<Tool
				Name="VCCustomBuildTool"
			/>
			<Tool
				Name="VCXMLDataGeneratorTool"
			/>
			<Tool
				Name="VCWebServiceProxyGeneratorTool"
			/>
			<Tool
				Name="VCMIDLTool"
			/>
			<Tool
				Name="VCCLCompilerTool"
				Optimization="2"
				EnableIntrinsicFunctions="true"
				AdditionalIncludeDirectories="&quot;\EZ_PATHlibEasea&quot;"
				PreprocessorDefinitions="WIN32;NDEBUG;_CONSOLE"
				RuntimeLibrary="0"
				EnableFunctionLevelLinking="true"
				UsePrecompiledHeader="0"
				WarningLevel="3"
				DebugInformationFormat="3"
			/>
			<Tool
				Name="VCManagedResourceCompilerTool"
			/>
			<Tool
				Name="VCResourceCompilerTool"
			/>
			<Tool
				Name="VCPreLinkEventTool"
			/>
			<Tool
				Name="VCLinkerTool"
				LinkIncremental="1"
				AdditionalLibraryDirectories="&quot;\EZ_PATHlibEasea&quot;"
				GenerateDebugInformation="true"
				SubSystem="1"
				OptimizeReferences="2"
				EnableCOMDATFolding="2"
				TargetMachine="1"
			/>
			<Tool
				Name="VCALinkTool"
			/>
			<Tool
				Name="VCManifestTool"
			/>
			<Tool
				Name="VCXDCMakeTool"
			/>
			<Tool
				Name="VCBscMakeTool"
			/>
			<Tool
				Name="VCFxCopTool"
			/>
			<Tool
				Name="VCAppVerifierTool"
			/>
			<Tool
				Name="VCPostBuildEventTool"
			/>
		</Configuration>
	</Configurations>
	<References>
	</References>
	<Files>
		<Filter
			Name="Source Files"
			Filter="cpp;c;cc;cxx;def;odl;idl;hpj;bat;asm;asmx"
			UniqueIdentifier="{4FC737F1-C7A5-4376-A066-2A32D752A2FF}"
			>
			<File
				RelativePath=".\EASEA.cpp"
				>
			</File>
			<File
				RelativePath=".\EASEAIndividual.cpp"
				>
			</File>
		</Filter>
		<Filter
			Name="Header Files"
			Filter="h;hpp;hxx;hm;inl;inc;xsd"
			UniqueIdentifier="{93995380-89BD-4b04-88EB-625FBE52EBFB}"
			>
			<File
				RelativePath=".\EASEAIndividual.hpp"
				>
			</File>
		</Filter>
		<Filter
			Name="Resource Files"
			Filter="rc;ico;cur;bmp;dlg;rc2;rct;bin;rgs;gif;jpg;jpeg;jpe;resx;tiff;tif;png;wav"
			UniqueIdentifier="{67DA6AB6-F800-4c08-8B7A-83BB121AAD01}"
			>
		</Filter>
	</Files>
	<Globals>
	</Globals>
</VisualStudioProject>

\START_EO_PARAM_TPL#****************************************
#                                         
#  EASEA.prm
#                                         
#  Parameter file generated by STD.tpl AESAE v1.0
#                                         
#***************************************
# --seed=0   # -S : Random number seed. It is possible to give a specific seed.

######    Evolution Engine    ######
--popSize=\POP_SIZE # -P : Population Size
--nbOffspring=\OFF_SIZE # -O : Nb of offspring (percentage or absolute)

######	  Stopping Criterions    #####
--nbGen=\NB_GEN #Nb of generations
--timeLimit=\TIME_LIMIT # Time Limit: desactivate with (0) (in Seconds)

######    Evolution Engine / Replacement    ######
--elite=\ELITE_SIZE  # Nb of elite parents (absolute)
--eliteType=\ELITISM # Strong (1) or weak (0) elitism (set elite to 0 for none)
--survivingParents=\SURV_PAR_SIZE # Nb of surviving parents (percentage or absolute)
--survivingOffspring=\SURV_OFF_SIZE  # Nb of surviving offspring (percentage or absolute)
--selectionOperator=\SELECTOR_OPERATOR # Selector: Deterministic, Tournament, Random, Roulette 
--selectionPressure=\SELECT_PRM
--reduceParentsOperator=\RED_PAR_OPERATOR 
--reduceParentsPressure=\RED_PAR_PRM
--reduceOffspringOperator=\RED_OFF_OPERATOR 
--reduceOffspringPressure=\RED_OFF_PRM
--reduceFinalOperator=\RED_FINAL_OPERATOR
--reduceFinalPressure=\RED_FINAL_PRM

#####	Stats Ouput 	#####
--printStats=\PRINT_STATS #print Stats to screen
--plotStats=\PLOT_STATS #plot Stats with gnuplot (requires Gnuplot)
--printInitialPopulation=0 #Print initial population
--printFinalPopulation=0 #Print final population
--generateCSV=\GENERATE_CSV_FILE
--generateGnuplotScript=\GENERATE_GNUPLOT_SCRIPT
--generateRScript=\GENERATE_R_SCRIPT

#### Population save	####
--savePopulation=\SAVE_POPULATION #save population to EASEA.pop file
--startFromFile=\START_FROM_FILE #start optimisation from EASEA.pop file
kruger's avatar
kruger committed
653
654
655
656

#### Remote Island Model ####
--remoteIslandModel=\REMOTE_ISLAND_MODEL #To initialize communications with remote AESAE's
--ipFile=\IP_FILE
kruger's avatar
kruger committed
657
\TEMPLATE_END