├── .gitignore
├── Chromosome.h
├── Common.h
├── Constants.h
├── DistanceType.h
├── GeneticAlgorithm.h
├── GeneticAlgorithmOptimizer.h
├── LICENSE
├── README.md
├── RotationDirection.h
├── RubiksColor.h
├── RubiksCube.h
├── RubiksCubeGA.cpp
├── RubiksSide.h
├── build.sh
└── selection.txt


/.gitignore:
--------------------------------------------------------------------------------
 1 | # Compiled Object files
 2 | *.slo
 3 | *.lo
 4 | *.o
 5 | *.obj
 6 | 
 7 | # Precompiled Headers
 8 | *.gch
 9 | *.pch
10 | 
11 | # Compiled Dynamic libraries
12 | *.so
13 | *.dylib
14 | *.dll
15 | 
16 | # Fortran module files
17 | *.mod
18 | 
19 | # Compiled Static libraries
20 | *.lai
21 | *.la
22 | *.a
23 | *.lib
24 | 
25 | # Executables
26 | *.exe
27 | *.out
28 | *.app
29 | 
30 | # Mac OS X
31 | .DS_Store
32 | 


--------------------------------------------------------------------------------
/Chromosome.h:
--------------------------------------------------------------------------------
 1 | #ifndef CHROMOSOME_H_INCLUDED
 2 | #define CHROMOSOME_H_INCLUDED
 3 | 
 4 | class Chromosome {
 5 | public:
 6 | 	double fitness;
 7 | 	std::string command;
 8 | 
 9 | 	Chromosome(std::string command, double fitness) {
10 | 		this->command = command;
11 | 		this->fitness = fitness;
12 | 	}
13 | 
14 | 	Chromosome(const Chromosome &chromosome) {
15 | 		(*this) = chromosome;
16 | 	}
17 | 
18 | 	Chromosome() {
19 | 		this->command = "";
20 | 		this->fitness = INVALID_FITNESS_VALUE;
21 | 	}
22 | 
23 | 	void operator=(const Chromosome &chromosome) {
24 | 		this->command = chromosome.command;
25 | 		this->fitness = chromosome.fitness;
26 | 	}
27 | };
28 | 
29 | #endif
30 | 


--------------------------------------------------------------------------------
/Common.h:
--------------------------------------------------------------------------------
 1 | #ifndef COMMON_H_INCLUDED
 2 | #define COMMON_H_INCLUDED
 3 | 
 4 | namespace std {
 5 | template < typename T > std::string to_string( const T& n ) {
 6 | 	std::ostringstream stm;
 7 | 	stm << n ;
 8 | 	return stm.str() ;
 9 | }
10 | }
11 | 
12 | #endif
13 | 


--------------------------------------------------------------------------------
/Constants.h:
--------------------------------------------------------------------------------
 1 | #ifndef CONSTANTS_H_INCLUDED
 2 | #define CONSTANTS_H_INCLUDED
 3 | 
 4 | #define ROOT_NODE 0
 5 | #define DEFAULT_TAG 0
 6 | 
 7 | #define RECEIVE_BUFFER_SIZE 100000
 8 | 
 9 | #define INVALID_FITNESS_VALUE INT_MAX
10 | 
11 | #define LOCAL_POPULATION_SIZE 37
12 | #define LOCAL_OPTIMIZATION_EPOCHES 10000
13 | 
14 | #define CHROMOSOMES_INITIAL_SIZE 1
15 | 
16 | #define CUBE_SHUFFLING_STEPS 10000
17 | 
18 | #define NUMBER_OF_BROADCASTS 47
19 | 
20 | #define COMMANDS_REDUCTION true
21 | 
22 | #define RANDOM_TRAVELER true
23 | 
24 | #endif
25 | 


--------------------------------------------------------------------------------
/DistanceType.h:
--------------------------------------------------------------------------------
 1 | #ifndef DISTANCETYPE_H_INCLUDED
 2 | #define DISTANCETYPE_H_INCLUDED
 3 | 
 4 | enum DistanceType {
 5 | 	EUCLIDEAN = 1,
 6 | 	WEIGHTED = 2,
 7 | 	HAUSDORFF = 3,
 8 | };
 9 | 
10 | #endif
11 | 


--------------------------------------------------------------------------------
/GeneticAlgorithm.h:
--------------------------------------------------------------------------------
  1 | #ifndef GENETICALGORITHM_H_INCLUDED
  2 | #define GENETICALGORITHM_H_INCLUDED
  3 | 
  4 | #include "Chromosome.h"
  5 | 
  6 | class GeneticAlgorithm {
  7 | private:
  8 | 	std::vector<Chromosome> population;
  9 | 	int resultIndex;
 10 | 	int firstIndex;
 11 | 	int secondIndex;
 12 | 	int bestIndex;
 13 | 	int worstIndex;
 14 | 
 15 | 	void selectRandom() {
 16 | 		do {
 17 | 			resultIndex = rand() % population.size();
 18 | 			firstIndex = rand() % population.size();
 19 | 			secondIndex = rand() % population.size();
 20 | 		} while(resultIndex==firstIndex || resultIndex==secondIndex || (resultIndex == bestIndex && KEEP_ELITE==true) || population[firstIndex].command.length()==0 || population[secondIndex].command.length()==0);
 21 | 	}
 22 | 
 23 | 	friend std::ostream& operator<< (std::ostream &out, const GeneticAlgorithm &ga);
 24 | 
 25 | public:
 26 | 	static const bool KEEP_ELITE = true;
 27 | 
 28 | public:
 29 | 	GeneticAlgorithm(int populationSize=0) {
 30 | 		if(populationSize < 0) {
 31 | 			populationSize = 0;
 32 | 		}
 33 | 		population.resize(populationSize);
 34 | 		resultIndex = 0;
 35 | 		firstIndex = 0;
 36 | 		secondIndex = 0;
 37 | 		bestIndex = 0;
 38 | 		worstIndex = 0;
 39 | 	}
 40 | 
 41 | 	GeneticAlgorithm(const GeneticAlgorithm &ga) {
 42 | 		(*this) = ga;
 43 | 	}
 44 | 
 45 | 	int getResultIndex() {
 46 | 		return( resultIndex );
 47 | 	}
 48 | 
 49 | 	int getBestIndex() {
 50 | 		return( bestIndex );
 51 | 	}
 52 | 
 53 | 	void setChromosome(Chromosome chromosome, int index=-1) {
 54 | 		if(index < -1) {
 55 | 			return;
 56 | 		}
 57 | 
 58 | 		if(index == -1) {
 59 | 			population.push_back( chromosome );
 60 | 			index = population.size() - 1;
 61 | 		} else if(index < population.size()) {
 62 | 			population[index] = chromosome;
 63 | 		}
 64 | 
 65 | 		if(population[index].fitness < population[bestIndex].fitness) {
 66 | 			bestIndex = index;
 67 | 		}
 68 | 		if(population[index].fitness > population[worstIndex].fitness) {
 69 | 			worstIndex = index;
 70 | 		}
 71 | 	}
 72 | 
 73 | 	const Chromosome& getChromosome(int index) const {
 74 | 		const static std::string EMPTY_STRING = "";
 75 | 
 76 | 		if(population.size() <= index || index <= -1) {
 77 | 			//TODO Handle exception.
 78 | 		}
 79 | 
 80 | 		return( population[index] );
 81 | 	}
 82 | 
 83 | 	const Chromosome& getBestChromosome() const {
 84 | 		return( population[bestIndex] );
 85 | 	}
 86 | 
 87 | 	const Chromosome& getRandomChromosome() const {
 88 | 		return( population[rand()%population.size()] );
 89 | 	}
 90 | 
 91 | 	const Chromosome& getWorstChromosome() const {
 92 | 		return( population[worstIndex] );
 93 | 	}
 94 | 
 95 | 	void replaceWorst(const Chromosome& chromosome) {
 96 | 		population[worstIndex] = chromosome;
 97 | 
 98 | 		bestIndex = 0;
 99 | 		worstIndex = 0;
100 | 		for(int i=0; i<population.size(); i++) {
101 | 			if(population[i].fitness < population[bestIndex].fitness) {
102 | 				bestIndex = i;
103 | 			}
104 | 			if(population[i].fitness > population[worstIndex].fitness) {
105 | 				worstIndex = i;
106 | 			}
107 | 		}
108 | 	}
109 | 
110 | 	void setFitness(double fitness, int index=-1) {
111 | 		if(index == -1) {
112 | 			index = population.size()-1;
113 | 		}
114 | 
115 | 		if(population.size() <= index) {
116 | 			//TODO Handle exception.
117 | 			return;
118 | 		}
119 | 
120 | 		population[index].fitness = fitness;
121 | 		if(fitness < population[bestIndex].fitness) {
122 | 			bestIndex = index;
123 | 		}
124 | 		if(fitness > population[worstIndex].fitness) {
125 | 			worstIndex = index;
126 | 		}
127 | 	}
128 | 
129 | 	double getFitness(int index) {
130 | 		if(population.size() <= index || index <= -1) {
131 | 			//TODO Handle exception.
132 | 			return( INVALID_FITNESS_VALUE );
133 | 		}
134 | 
135 | 		return( population[index].fitness );
136 | 	}
137 | 
138 | 	double getBestFitness() const {
139 | 		return( population[bestIndex].fitness );
140 | 	}
141 | 
142 | 	int size() {
143 | 		return( population.size() );
144 | 	}
145 | 
146 | 	void subset(GeneticAlgorithm &ga, const int size) const {
147 | 		if(population.size() <= 0) {
148 | 			return;
149 | 		}
150 | 
151 | 		for(int i=0; i<size; i++) {
152 | 			ga.setChromosome( population[ rand()%population.size() ] );
153 | 		}
154 | 	}
155 | 
156 | 	void selection() {
157 | 		static const int CROSSOVER_RESULT_INTO_BEST_PERCENT = 1;
158 | 		static const int CROSSOVER_RESULT_INTO_MIDDLE_PERCENT = 9;
159 | 		static const int CROSSOVER_RESULT_INTO_WORST_PERCENT = 90;
160 | 
161 | 		static int percent = -1;
162 | 		percent = rand()
163 | 				  % (CROSSOVER_RESULT_INTO_WORST_PERCENT
164 | 					 + CROSSOVER_RESULT_INTO_MIDDLE_PERCENT
165 | 					 + CROSSOVER_RESULT_INTO_BEST_PERCENT);
166 | 
167 | 		if (percent < CROSSOVER_RESULT_INTO_WORST_PERCENT) {
168 | 			do {
169 | 				selectRandom();
170 | 			} while (population[resultIndex].fitness < population[firstIndex].fitness
171 | 					 || population[resultIndex].fitness < population[secondIndex].fitness);
172 | 		} else if (percent
173 | 				   < (CROSSOVER_RESULT_INTO_WORST_PERCENT
174 | 					  + CROSSOVER_RESULT_INTO_MIDDLE_PERCENT)) {
175 | 			do {
176 | 				selectRandom();
177 | 			} while (population[resultIndex].fitness < population[firstIndex].fitness
178 | 					 || population[resultIndex].fitness > population[secondIndex].fitness);
179 | 		} else if (percent
180 | 				   < (CROSSOVER_RESULT_INTO_WORST_PERCENT
181 | 					  + CROSSOVER_RESULT_INTO_MIDDLE_PERCENT
182 | 					  + CROSSOVER_RESULT_INTO_BEST_PERCENT)) {
183 | 			do {
184 | 				selectRandom();
185 | 			} while (population[resultIndex].fitness > population[firstIndex].fitness
186 | 					 || population[resultIndex].fitness > population[secondIndex].fitness);
187 | 		}
188 | 	}
189 | 
190 | 	void crossover() {
191 | 		population[resultIndex].command = population[firstIndex].command.substr(0, rand()%(population[firstIndex].command.length())+1);
192 | 		population[resultIndex].command += population[secondIndex].command.substr(rand()%population[secondIndex].command.length(), population[secondIndex].command.length());
193 | 		population[resultIndex].fitness = INVALID_FITNESS_VALUE;
194 | 	}
195 | 
196 | 	void mutation() {
197 | 		int index = rand() % population[resultIndex].command.length();
198 | 
199 | 		switch(rand()%6) {
200 | 		case 0:
201 | 			population[resultIndex].command[index]=(char)TOP;
202 | 			break;
203 | 		case 1:
204 | 			population[resultIndex].command[index]=(char)LEFT;
205 | 			break;
206 | 		case 2:
207 | 			population[resultIndex].command[index]=(char)RIGHT;
208 | 			break;
209 | 		case 3:
210 | 			population[resultIndex].command[index]=(char)FRONT;
211 | 			break;
212 | 		case 4:
213 | 			population[resultIndex].command[index]=(char)BACK;
214 | 			break;
215 | 		case 5:
216 | 			population[resultIndex].command[index]=(char)DOWN;
217 | 			break;
218 | 		}
219 | 
220 | 		population[resultIndex].fitness = INVALID_FITNESS_VALUE;
221 | 	}
222 | 
223 | 	void reduction() {
224 | 		static const char nop[] = {NONE, '\0'};
225 | 
226 | 		if(COMMANDS_REDUCTION == false) {
227 | 			return;
228 | 		}
229 | 
230 | 		bool done = true;
231 | 		std::string &value = population[resultIndex].command;
232 | 
233 | 		do {
234 | 			done = true;
235 | 
236 | 			for(int i=1, j=0; i<value.size(); i++) {
237 | 				if(value[i] == value[i-1]) {
238 | 					j++;
239 | 				} else {
240 | 					j = 0;
241 | 				}
242 | 
243 | 				if(j == 3) {
244 | 					done = false;
245 | 					value = value.substr(0,i-3) + nop + value.substr(i+1);
246 | 
247 | 					j = 0;
248 | 					i -= 3;
249 | 				}
250 | 			}
251 | 		} while(done == false);
252 | 	}
253 | 
254 | 	const std::string& toString() {
255 | 		static std::string result;
256 | 		result = "";
257 | 
258 | 		/* Keep population size. */
259 | 		result += std::to_string(population.size());
260 | 		result += " ";
261 | 
262 | 		for(int i=0; i<population.size(); i++) {
263 | 			result += std::to_string(population[i].fitness);
264 | 			result += " ";
265 | 			if(population[i].command == "") {
266 | 				result += NONE;
267 | 			} else {
268 | 				result += population[i].command;
269 | 			}
270 | 			result += " ";
271 | 		}
272 | 
273 | 		/* Trim spaces. */
274 | 		result.erase(result.size()-1, 1);
275 | 		result += '\0';
276 | 
277 | 		return result;
278 | 	}
279 | 
280 | 	void fromString(const char text[]) {
281 | 		std::string buffer(text);
282 | 		std::istringstream in(buffer);
283 | 
284 | 		population.clear();
285 | 		bestIndex = 0;
286 | 		worstIndex = 0;
287 | 
288 | 		int size = 0;
289 | 		in >> size;
290 | 
291 | 		double value;
292 | 		std::string commands;
293 | 		for(int i=0; i<size; i++) {
294 | 			in >> value;
295 | 			in >> commands;
296 | 
297 | 			setChromosome(Chromosome(commands,value));
298 | 
299 | 			if(population[bestIndex].fitness > population[i].fitness) {
300 | 				bestIndex = i;
301 | 			}
302 | 			if(population[worstIndex].fitness < population[i].fitness) {
303 | 				worstIndex = i;
304 | 			}
305 | 		}
306 | 	}
307 | 
308 | 	void operator=(const GeneticAlgorithm &ga) {
309 | 		this->population.clear();
310 | 
311 | 		this->population = ga.population;
312 | 		this->resultIndex = ga.resultIndex;
313 | 		this->firstIndex = ga.firstIndex;
314 | 		this->secondIndex = ga.secondIndex;
315 | 		this->bestIndex = ga.bestIndex;
316 | 		this->worstIndex = ga.worstIndex;
317 | 	}
318 | };
319 | 
320 | std::ostream& operator<< (std::ostream &out, const GeneticAlgorithm &ga) {
321 | 	for(int p=0; p<ga.population.size(); p++) {
322 | 		out << ga.population[p].fitness;
323 | 		out << "\t";
324 | 		for(int i=0; i<ga.population[p].command.length(); i++) {
325 | 			out << ga.population[p].command[i];
326 | 		}
327 | 		out << std::endl;
328 | 	}
329 | 
330 | 	return out;
331 | }
332 | 
333 | #endif
334 | 


--------------------------------------------------------------------------------
/GeneticAlgorithmOptimizer.h:
--------------------------------------------------------------------------------
 1 | #ifndef GENETICALGORITHMOPTIMIZER_H_INCLUDED
 2 | #define GENETICALGORITHMOPTIMIZER_H_INCLUDED
 3 | 
 4 | #include "RubiksSide.h"
 5 | 
 6 | class GeneticAlgorithmOptimizer {
 7 | private:
 8 | 	static double evaluate(const RubiksCube &solved, const RubiksCube &shuffled, const std::string &commands) {
 9 | 		static RubiksCube used;
10 | 
11 | 		used = shuffled;
12 | 		used.execute(commands);
13 | 		return( solved.compare(used) );
14 | 	}
15 | 
16 | 	GeneticAlgorithmOptimizer() {
17 | 	}
18 | 
19 | public:
20 | 	static void addRandomCommands(GeneticAlgorithm &ga, const RubiksCube &solved, const RubiksCube &shuffled, int populationSize=0) {
21 | 		for(int p=0; p<populationSize; p++) {
22 | 			RubiksCube mixed;
23 | 			std::string commands = mixed.shuffle(CHROMOSOMES_INITIAL_SIZE);
24 | 			ga.setChromosome( Chromosome(commands,INVALID_FITNESS_VALUE) );
25 | 			ga.setFitness(evaluate(solved, shuffled, commands));
26 | 		}
27 | 	}
28 | 
29 | 	static void addEmptyCommand(GeneticAlgorithm &ga, const RubiksCube &solved, const RubiksCube &shuffled) {
30 | 		static const char value[] = {NONE, '\0'};
31 | 		ga.setChromosome(Chromosome(std::string(value),INVALID_FITNESS_VALUE));
32 | 		ga.setFitness(evaluate(solved, shuffled, std::string(value)));
33 | 	}
34 | 
35 | 	static void optimize(GeneticAlgorithm &ga, RubiksCube &solved, RubiksCube &shuffled, long epoches=0) {
36 | 		for(long e=0L; e<epoches*ga.size(); e++) {
37 | 			ga.selection();
38 | 			ga.crossover();
39 | 			ga.mutation();
40 | 			ga.reduction();
41 | 			int index = ga.getResultIndex();
42 | 			ga.setFitness(evaluate(solved, shuffled, ga.getChromosome(index).command), index);
43 | 		}
44 | 
45 | 		shuffled.execute(ga.getChromosome(ga.getBestIndex()).command);
46 | 	}
47 | };
48 | 
49 | #endif
50 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
  1 |                     GNU GENERAL PUBLIC LICENSE
  2 |                        Version 3, 29 June 2007
  3 | 
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676 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # RubiksCubeGeneticAlgorithmsSolver
2 | 
3 | MPI parallel implementation of genetic algorithm based Rubik's cube solver.
4 | 
5 | Acknowledgements
6 | 
7 | This work was supported by a grant of the Bulgarian National Scientific Fund under the grants DFNI 02/20 Efficient Parallel Algorithms for Large Scale Computational Problems and DFNI 02/5 InterCriteria Analysis A New Approach to Decision Making.
8 | 


--------------------------------------------------------------------------------
/RotationDirection.h:
--------------------------------------------------------------------------------
 1 | #ifndef ROTATIONDIRECTION_H_INCLUDED
 2 | #define ROTATIONDIRECTION_H_INCLUDED
 3 | 
 4 | enum RotationDirection {
 5 | 	COUNTERCLOCKWISE = -1,
 6 | 	CLOCKWISE = +1
 7 | };
 8 | 
 9 | #endif
10 | 


--------------------------------------------------------------------------------
/RubiksColor.h:
--------------------------------------------------------------------------------
 1 | #ifndef RUBIKSCOLOR_H_INCLUDED
 2 | #define RUBIKSCOLOR_H_INCLUDED
 3 | 
 4 | enum RubiksColor {
 5 | 	BLANK = 0,
 6 | 	RED = 1,
 7 | 	BLUE = 2,
 8 | 	YELLOW = 3,
 9 | 	WHITE = 4,
10 | 	GREEN = 5,
11 | 	PURPLE = 6,
12 | };
13 | 
14 | #endif
15 | 


--------------------------------------------------------------------------------
/RubiksCube.h:
--------------------------------------------------------------------------------
  1 | #ifndef RUBIKSCUBE_H_INCLUDED
  2 | #define RUBIKSCUBE_H_INCLUDED
  3 | 
  4 | #include "Common.h"
  5 | #include "RubiksSide.h"
  6 | #include "RubiksColor.h"
  7 | #include "DistanceType.h"
  8 | #include "RotationDirection.h"
  9 | 
 10 | class RubiksCube {
 11 | private:
 12 | 	int top[3][3];
 13 | 	int left[3][3];
 14 | 	int right[3][3];
 15 | 	int front[3][3];
 16 | 	int back[3][3];
 17 | 	int down[3][3];
 18 | 
 19 | 	int (*sides[6])[3][3];
 20 | 
 21 | 	std::string result;
 22 | 
 23 | 	DistanceType distance = EUCLIDEAN;
 24 | 
 25 | 	void spinSide(RubiksSide side) {
 26 | 		static int buffer[ 3 ];
 27 | 
 28 | 		if (side == TOP) {
 29 | 			for (int i = 0; i < 3; i++) {
 30 | 				buffer[i] = left[i][2];
 31 | 			}
 32 | 			for (int i = 0; i < 3; i++) {
 33 | 				left[i][2] = front[0][i];
 34 | 			}
 35 | 			for (int i = 0; i < 3; i++) {
 36 | 				front[0][i] = right[3 - i - 1][0];
 37 | 			}
 38 | 			for (int i = 0; i < 3; i++) {
 39 | 				right[i][0] = back[2][i];
 40 | 			}
 41 | 			for (int i = 0; i < 3; i++) {
 42 | 				back[2][3 - i - 1] = buffer[i];
 43 | 			}
 44 | 		} else if (side == LEFT) {
 45 | 			for (int i = 0; i < 3; i++) {
 46 | 				buffer[i] = down[i][2];
 47 | 			}
 48 | 			for (int i = 0; i < 3; i++) {
 49 | 				down[3 - i - 1][2] = front[i][0];
 50 | 			}
 51 | 			for (int i = 0; i < 3; i++) {
 52 | 				front[i][0] = top[i][0];
 53 | 			}
 54 | 			for (int i = 0; i < 3; i++) {
 55 | 				top[i][0] = back[i][0];
 56 | 			}
 57 | 			for (int i = 0; i < 3; i++) {
 58 | 				back[3 - i - 1][0] = buffer[i];
 59 | 			}
 60 | 		} else if (side == BACK) {
 61 | 			for (int i = 0; i < 3; i++) {
 62 | 				buffer[i] = down[0][i];
 63 | 			}
 64 | 			for (int i = 0; i < 3; i++) {
 65 | 				down[0][i] = left[0][i];
 66 | 			}
 67 | 			for (int i = 0; i < 3; i++) {
 68 | 				left[0][i] = top[0][i];
 69 | 			}
 70 | 			for (int i = 0; i < 3; i++) {
 71 | 				top[0][i] = right[0][i];
 72 | 			}
 73 | 			for (int i = 0; i < 3; i++) {
 74 | 				right[0][i] = buffer[i];
 75 | 			}
 76 | 		} else if (side == RIGHT) {
 77 | 			for (int i = 0; i < 3; i++) {
 78 | 				buffer[i] = down[i][0];
 79 | 			}
 80 | 			for (int i = 0; i < 3; i++) {
 81 | 				down[i][0] = back[3 - i - 1][2];
 82 | 			}
 83 | 			for (int i = 0; i < 3; i++) {
 84 | 				back[i][2] = top[i][2];
 85 | 			}
 86 | 			for (int i = 0; i < 3; i++) {
 87 | 				top[i][2] = front[i][2];
 88 | 			}
 89 | 			for (int i = 0; i < 3; i++) {
 90 | 				front[3 - i - 1][2] = buffer[i];
 91 | 			}
 92 | 		} else if (side == FRONT) {
 93 | 			for (int i = 0; i < 3; i++) {
 94 | 				buffer[i] = down[2][i];
 95 | 			}
 96 | 			for (int i = 0; i < 3; i++) {
 97 | 				down[2][i] = right[2][i];
 98 | 			}
 99 | 			for (int i = 0; i < 3; i++) {
100 | 				right[2][i] = top[2][i];
101 | 			}
102 | 			for (int i = 0; i < 3; i++) {
103 | 				top[2][i] = left[2][i];
104 | 			}
105 | 			for (int i = 0; i < 3; i++)
106 | 				left[2][i] = buffer[i];
107 | 		} else if (side == DOWN) {
108 | 			for (int i = 0; i < 3; i++) {
109 | 				buffer[i] = front[2][i];
110 | 			}
111 | 			for (int i = 0; i < 3; i++) {
112 | 				front[2][i] = left[i][0];
113 | 			}
114 | 			for (int i = 0; i < 3; i++) {
115 | 				left[i][0] = back[0][3 - i - 1];
116 | 			}
117 | 			for (int i = 0; i < 3; i++) {
118 | 				back[0][i] = right[i][2];
119 | 			}
120 | 			for (int i = 0; i < 3; i++) {
121 | 				right[3 - i - 1][2] = buffer[i];
122 | 			}
123 | 		}
124 | 	}
125 | 
126 | 	void spinClockwise(int side[3][3], int times, RubiksSide index) {
127 | 		static int buffer[3][3];
128 | 		static int newarray[3][3];
129 | 
130 | 		if (times == 0) {
131 | 			return;
132 | 		}
133 | 
134 | 		/* Transponse. */
135 | 		for (int j = 0; j < 3; j++) {
136 | 			for (int i = 0; i < 3; i++) {
137 | 				newarray[j][i] = side[i][j];
138 | 			}
139 | 		}
140 | 		/* Rearrange. */
141 | 		for (int i = 0; i < 3; i++) {
142 | 			static int cache = 0;
143 | 			cache = newarray[i][0];
144 | 			newarray[i][0] = newarray[i][2];
145 | 			newarray[i][2] = cache;
146 | 		}
147 | 
148 | 		spinSide(index);
149 | 		memcpy(buffer, newarray, sizeof(int)*3*3);
150 | 
151 | 		for (int t = 1; t < times; t++) {
152 | 			for (int j = 0; j < 3; j++) {
153 | 				for (int i = 0; i < 3; i++) {
154 | 					newarray[j][i] = buffer[i][j];
155 | 				}
156 | 			}
157 | 			for (int i = 0; i < 3; i++) {
158 | 				static int cache = 0;
159 | 				cache = newarray[i][0];
160 | 				newarray[i][0] = newarray[i][2];
161 | 				newarray[i][2] = cache;
162 | 			}
163 | 
164 | 			spinSide(index);
165 | 
166 | 			memcpy(buffer, newarray, sizeof(int)*3*3);
167 | 		}
168 | 
169 | 		memcpy(side, buffer, sizeof(int)*3*3);
170 | 	}
171 | 
172 | 	double euclidean(const RubiksCube &cube) const {
173 | 		double distance = 0.0;
174 | 
175 | 		for(int i=0; i<3; i++) {
176 | 			for(int j=0; j<3; j++) {
177 | 				distance += (top[i][j]-cube.top[i][j])*(top[i][j]-cube.top[i][j]);
178 | 				distance += (left[i][j]-cube.left[i][j])*(left[i][j]-cube.left[i][j]);
179 | 				distance += (right[i][j]-cube.right[i][j])*(right[i][j]-cube.right[i][j]);
180 | 				distance += (front[i][j]-cube.front[i][j])*(front[i][j]-cube.front[i][j]);
181 | 				distance += (back[i][j]-cube.back[i][j])*(back[i][j]-cube.back[i][j]);
182 | 				distance += (down[i][j]-cube.down[i][j])*(down[i][j]-cube.down[i][j]);
183 | 			}
184 | 		}
185 | 
186 | 		return sqrt(distance);
187 | 	}
188 | 
189 | 	double colors(const RubiksCube &cube) const {
190 | 		//TODO Change array with STL maps.
191 | 		static const double coefficients[7][7] = {
192 | 			{0, 0, 0, 0, 0, 0, 0},
193 | 			{0, 1, 2, 2, 2, 2, 4},
194 | 			{0, 2, 1, 2, 4, 2, 2},
195 | 			{0, 2, 2, 1, 2, 4, 2},
196 | 			{0, 2, 4, 2, 1, 2, 2},
197 | 			{0, 2, 2, 4, 2, 1, 2},
198 | 			{0, 4, 2, 2, 2, 2, 1},
199 | 		};
200 | 
201 | 		double distance = 0.0;
202 | 
203 | 		/* Count matches for all sides. */
204 | 		for(int s=0; s<6; s++) {
205 | 			for(int i=0; i<3; i++) {
206 | 				for(int j=0; j<3; j++) {
207 | 					/* If colors are equal calculate distance. */
208 | 					distance += coefficients[(*sides[s])[1][1]][(*sides[s])[i][j]];
209 | 				}
210 | 			}
211 | 		}
212 | 
213 | 		return distance;
214 | 	}
215 | 
216 | 	double euclidean(const int side1[3][3], const int side2[3][3]) const {
217 | 		double distance = 0.0;
218 | 
219 | 		for(int i=0; i<3; i++) {
220 | 			for(int j=0; j<3; j++) {
221 | 				distance += (side1[i][j]-side2[i][j])*(side1[i][j]-side2[i][j]);
222 | 			}
223 | 		}
224 | 
225 | 		return sqrt(distance);
226 | 	}
227 | 
228 | 	double hausdorff(const RubiksCube &cube) const {
229 | 		/* Minimums should be found for each side. */
230 | 		double min[] = {INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX, INT_MAX};
231 | 
232 | 		/* Check all sides in pairs. */
233 | 		for(int s1=0; s1<6; s1++) {
234 | 			for(int s2=0; s2<6; s2++) {
235 | 				double distance
236 | 					= euclidean(*sides[s1], *(cube.sides)[s2]);
237 | 
238 | 				/* Keep track for the minimum distance. */
239 | 				if(min[s1] > distance) {
240 | 					min[s1] = distance;
241 | 				}
242 | 			}
243 | 		}
244 | 
245 | 		/* Find the maximum between the minimums. */
246 | 		double result = min[0];
247 | 		for(int s1=0; s1<6; s1++) {
248 | 			if(result < min[s1]) {
249 | 				result = min[s1];
250 | 			}
251 | 		}
252 | 
253 | 		return(result);
254 | 	}
255 | 
256 | 	friend std::ostream& operator<< (std::ostream &out, const RubiksCube &cube);
257 | 
258 | public:
259 | 	RubiksCube() {
260 | 		reset();
261 | 
262 | 		sides[0] = &top;
263 | 		sides[1] = &left;
264 | 		sides[2] = &right;
265 | 		sides[3] = &front;
266 | 		sides[4] = &back;
267 | 		sides[5] = &down;
268 | 	}
269 | 
270 | 	void reset() {
271 | 		for(int i=0; i<3; i++) {
272 | 			for(int j=0; j<3; j++) {
273 | 				top[i][j] = GREEN;
274 | 				left[i][j] = PURPLE;
275 | 				right[i][j] = RED;
276 | 				front[i][j] = WHITE;
277 | 				back[i][j] = YELLOW;
278 | 				down[i][j] = BLUE;
279 | 			}
280 | 		}
281 | 	}
282 | 
283 | 	void setDistanceType(DistanceType type) {
284 | 		distance = type;
285 | 	}
286 | 
287 | 	double compare(const RubiksCube &cube) const {
288 | 		switch(distance) {
289 | 		case
290 | 				EUCLIDEAN:
291 | 			return euclidean(cube);
292 | 			break;
293 | 		case
294 | 				WEIGHTED:
295 | 			return colors(cube);
296 | 			break;
297 | 		case
298 | 				HAUSDORFF:
299 | 			return hausdorff(cube);
300 | 			break;
301 | 		default:
302 | 			//TODO Do exception handling.
303 | 			break;
304 | 		}
305 | 	}
306 | 
307 | 	void callSpin(RubiksSide side, RotationDirection direction, int numberOfTimes) {
308 | 		if (numberOfTimes < 0) {
309 | 			numberOfTimes = -numberOfTimes;
310 | 			if(direction == CLOCKWISE) {
311 | 				direction = COUNTERCLOCKWISE;
312 | 			} else if(direction == COUNTERCLOCKWISE) {
313 | 				direction = CLOCKWISE;
314 | 			}
315 | 		}
316 | 
317 | 		numberOfTimes %= 4;
318 | 
319 | 		if (direction == CLOCKWISE) {
320 | 			if (side == NONE) {
321 | 				/* Do nothing. */
322 | 			}
323 | 			if (side == TOP) {
324 | 				spinClockwise(top, numberOfTimes, TOP);
325 | 			}
326 | 			if (side == LEFT) {
327 | 				spinClockwise(left, numberOfTimes, LEFT);
328 | 			}
329 | 			if (side == RIGHT) {
330 | 				spinClockwise(right, numberOfTimes, RIGHT);
331 | 			}
332 | 			if (side == FRONT) {
333 | 				spinClockwise(front, numberOfTimes, FRONT);
334 | 			}
335 | 			if (side == BACK) {
336 | 				spinClockwise(back, numberOfTimes, BACK);
337 | 			}
338 | 			if (side == DOWN) {
339 | 				spinClockwise(down, numberOfTimes, DOWN);
340 | 			}
341 | 		}
342 | 	}
343 | 
344 | 	void execute(std::string commands) {
345 | 		for(int i=0; i<commands.length(); i++) {
346 | 			callSpin((RubiksSide)commands[i], CLOCKWISE, 1);
347 | 		}
348 | 	}
349 | 
350 | 	std::string shuffle(int numberOfMoves=0) {
351 | 		std::string commands = "";
352 | 
353 | 		for(int i=0; i<numberOfMoves; i++) {
354 | 			switch(rand()%6) {
355 | 			case 0:
356 | 				commands+=(char)TOP;
357 | 				break;
358 | 			case 1:
359 | 				commands+=(char)LEFT;
360 | 				break;
361 | 			case 2:
362 | 				commands+=(char)RIGHT;
363 | 				break;
364 | 			case 3:
365 | 				commands+=(char)FRONT;
366 | 				break;
367 | 			case 4:
368 | 				commands+=(char)BACK;
369 | 				break;
370 | 			case 5:
371 | 				commands+=(char)DOWN;
372 | 				break;
373 | 			}
374 | 		}
375 | 
376 | 		execute(commands);
377 | 
378 | 		return commands;
379 | 	}
380 | 
381 | 	const std::string& toString() {
382 | 		result = "";
383 | 
384 | 		for(int i=0; i<3; i++) {
385 | 			for(int j=0; j<3; j++) {
386 | 				result += std::to_string(top[i][j]) + " ";
387 | 			}
388 | 		}
389 | 		for(int i=0; i<3; i++) {
390 | 			for(int j=0; j<3; j++) {
391 | 				result += std::to_string(left[i][j]) + " ";
392 | 			}
393 | 		}
394 | 		for(int i=0; i<3; i++) {
395 | 			for(int j=0; j<3; j++) {
396 | 				result += std::to_string(right[i][j]) + " ";
397 | 			}
398 | 		}
399 | 		for(int i=0; i<3; i++) {
400 | 			for(int j=0; j<3; j++) {
401 | 				result += std::to_string(front[i][j]) + " ";
402 | 			}
403 | 		}
404 | 		for(int i=0; i<3; i++) {
405 | 			for(int j=0; j<3; j++) {
406 | 				result += std::to_string(back[i][j]) + " ";
407 | 			}
408 | 		}
409 | 		for(int i=0; i<3; i++) {
410 | 			for(int j=0; j<3; j++) {
411 | 				result += std::to_string(down[i][j]) + " ";
412 | 			}
413 | 		}
414 | 
415 | 		/* Trim spaces. */
416 | 		result.erase(result.size()-1, 1);
417 | 		result += '\0';
418 | 
419 | 		return result;
420 | 	}
421 | 
422 | 	void fromString(const char text[]) {
423 | 		std::string buffer(text);
424 | 		std::istringstream in(buffer);
425 | 
426 | 		for(int i=0; i<3; i++) {
427 | 			for(int j=0; j<3; j++) {
428 | 				in >> top[i][j];
429 | 			}
430 | 		}
431 | 		for(int i=0; i<3; i++) {
432 | 			for(int j=0; j<3; j++) {
433 | 				in >> left[i][j];
434 | 			}
435 | 		}
436 | 		for(int i=0; i<3; i++) {
437 | 			for(int j=0; j<3; j++) {
438 | 				in >> right[i][j];
439 | 			}
440 | 		}
441 | 		for(int i=0; i<3; i++) {
442 | 			for(int j=0; j<3; j++) {
443 | 				in >> front[i][j];
444 | 			}
445 | 		}
446 | 		for(int i=0; i<3; i++) {
447 | 			for(int j=0; j<3; j++) {
448 | 				in >> back[i][j];
449 | 			}
450 | 		}
451 | 		for(int i=0; i<3; i++) {
452 | 			for(int j=0; j<3; j++) {
453 | 				in >> down[i][j];
454 | 			}
455 | 		}
456 | 	}
457 | };
458 | 
459 | std::ostream& operator<< (std::ostream &out, const RubiksCube &cube) {
460 | 	for(int i=0; i<3; i++) {
461 | 		out << "      ";
462 | 		for(int j=0; j<3; j++) {
463 | 			out << cube.back[i][j] << " ";
464 | 		}
465 | 		out << std::endl;
466 | 	}
467 | 
468 | 	for(int i=0; i<3; i++) {
469 | 		for(int j=0; j<3; j++) {
470 | 			out << cube.left[i][j] << " ";
471 | 		}
472 | 		for(int j=0; j<3; j++) {
473 | 			out << cube.top[i][j] << " ";
474 | 		}
475 | 		for(int j=0; j<3; j++) {
476 | 			out << cube.right[i][j] << " ";
477 | 		}
478 | 		for(int j=0; j<3; j++) {
479 | 			out << cube.down[i][j] << " ";
480 | 		}
481 | 		out << std::endl;
482 | 	}
483 | 
484 | 	for(int i=0; i<3; i++) {
485 | 		out << "      ";
486 | 		for(int j=0; j<3; j++) {
487 | 			out << cube.front[i][j] << " ";
488 | 		}
489 | 		out << std::endl;
490 | 	}
491 | 
492 | 	return out;
493 | }
494 | 
495 | #endif
496 | 


--------------------------------------------------------------------------------
/RubiksCubeGA.cpp:
--------------------------------------------------------------------------------
  1 | #include <map>
  2 | #include <cmath>
  3 | #include <vector>
  4 | #include <climits>
  5 | #include <cstdlib>
  6 | #include <cstring>
  7 | #include <ostream>
  8 | #include <sstream>
  9 | #include <iostream>
 10 | 
 11 | #include <mpi.h>
 12 | #include <unistd.h>
 13 | 
 14 | #include "Common.h"
 15 | #include "Constants.h"
 16 | #include "RubiksCube.h"
 17 | #include "GeneticAlgorithm.h"
 18 | #include "GeneticAlgorithmOptimizer.h"
 19 | 
 20 | static int rank = -1;
 21 | static int size = 0;
 22 | 
 23 | /** Receive buffer. */
 24 | static char buffer[RECEIVE_BUFFER_SIZE];
 25 | 
 26 | static RubiksCube solved;
 27 | static RubiksCube shuffled;
 28 | 
 29 | static void shuffle() {
 30 | 	if(rank != ROOT_NODE) {
 31 | 		return;
 32 | 	}
 33 | 
 34 | 	/* Cube to be solved. */
 35 | 	shuffled.shuffle(CUBE_SHUFFLING_STEPS);
 36 | 	std::cout << "Sender : " << std::to_string(shuffled.compare(solved)) << std::endl;
 37 | }
 38 | 
 39 | static void master1() {
 40 | 	unsigned long counter = 0;
 41 | 
 42 | 	if(rank != ROOT_NODE) {
 43 | 		return;
 44 | 	}
 45 | 
 46 | 	/* Send shffled cube to all other nodes. */ {
 47 | 		const std::string &value = shuffled.toString();
 48 | 		for(int r=0; r<size; r++) {
 49 | 			/* Root node is not included. */
 50 | 			if(r == ROOT_NODE) {
 51 | 				continue;
 52 | 			}
 53 | 
 54 | 			MPI_Send(value.c_str(), value.size(), MPI_BYTE, r, DEFAULT_TAG, MPI_COMM_WORLD);
 55 | 		}
 56 | 	}
 57 | 
 58 | 	std::map<int,GeneticAlgorithm> populations;
 59 | 	do {
 60 | 		std::cout << "Round : " << (counter+1) << std::endl;
 61 | 
 62 | 		/* Send GA population to all other nodes. */
 63 | 		for(int r=0; r<size; r++) {
 64 | 			/* Root node is not included. */
 65 | 			if(r == ROOT_NODE) {
 66 | 				continue;
 67 | 			}
 68 | 
 69 | 			GeneticAlgorithm ga;
 70 | 			if(counter == 0) {
 71 | 				GeneticAlgorithmOptimizer::addEmptyCommand(ga, solved, shuffled);
 72 | 				GeneticAlgorithmOptimizer::addRandomCommands(ga, solved, shuffled, LOCAL_POPULATION_SIZE);
 73 | 				populations[r] = ga;
 74 | 			} else {
 75 | 				/* Ring migration strategy. */
 76 | 				int next = (r+1) % size;
 77 | 				while(next == ROOT_NODE) {
 78 | 					next = (next+1) % size;
 79 | 				}
 80 | 
 81 | 				if(RANDOM_TRAVELER == true) {
 82 | 					populations[r].replaceWorst(populations[next].getRandomChromosome());
 83 | 				} else {
 84 | 					populations[r].replaceWorst(populations[next].getBestChromosome());
 85 | 				}
 86 | 			}
 87 | 			const std::string &value = populations[r].toString();
 88 | 			MPI_Send(value.c_str(), value.size(), MPI_BYTE, r, DEFAULT_TAG, MPI_COMM_WORLD);
 89 | 		}
 90 | 
 91 | 		/* Collect results from all other nodes. */
 92 | 		for(int r=0; r<size; r++) {
 93 | 			/* Root node is not included. */
 94 | 			if(r == ROOT_NODE) {
 95 | 				continue;
 96 | 			}
 97 | 
 98 | 			GeneticAlgorithm ga;
 99 | 			MPI_Recv(buffer, RECEIVE_BUFFER_SIZE, MPI_BYTE, r, DEFAULT_TAG, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
100 | 			ga.fromString(buffer);
101 | 			populations[r] = ga;
102 | 			std::cout << "Worker " << r << " : " << ga.getBestChromosome().fitness << std::endl;
103 | 		}
104 | 
105 | 		counter++;
106 | 	} while(counter < NUMBER_OF_BROADCASTS);
107 | }
108 | 
109 | static void master2() {
110 | 	unsigned long counter = 0;
111 | 
112 | 	if(rank != ROOT_NODE) {
113 | 		return;
114 | 	}
115 | 
116 | 	/* Send shffled cube to all other nodes. */ {
117 | 		const std::string &value = shuffled.toString();
118 | 		for(int r=0; r<size; r++) {
119 | 			/* Root node is not included. */
120 | 			if(r == ROOT_NODE) {
121 | 				continue;
122 | 			}
123 | 
124 | 			MPI_Send(value.c_str(), value.size(), MPI_BYTE, r, DEFAULT_TAG, MPI_COMM_WORLD);
125 | 		}
126 | 	}
127 | 
128 | 	GeneticAlgorithm global;
129 | 	std::map<int,GeneticAlgorithm> populations;
130 | 	do {
131 | 		std::cout << "Round : " << (counter+1) << std::endl;
132 | 
133 | 		for(int r=0; r<size; r++) {
134 | 			/* Root node is not included. */
135 | 			if(r == ROOT_NODE) {
136 | 				continue;
137 | 			}
138 | 
139 | 			if(counter == 0) {
140 | 				GeneticAlgorithmOptimizer::addEmptyCommand(global, solved, shuffled);
141 | 				GeneticAlgorithmOptimizer::addRandomCommands(global, solved, shuffled, LOCAL_POPULATION_SIZE*size);
142 | 				GeneticAlgorithm ga;
143 | 				global.subset(ga, LOCAL_POPULATION_SIZE);
144 | 				populations[r] = ga;
145 | 			} else {
146 | 				//TODO Find better way to control this probability.
147 | 				if(rand()%(NUMBER_OF_BROADCASTS/10) == 0) {
148 | 					GeneticAlgorithm ga;
149 | 					global.subset(ga, LOCAL_POPULATION_SIZE);
150 | 					populations[r] = ga;
151 | 				}
152 | 			}
153 | 			const std::string &value = populations[r].toString();
154 | 			MPI_Send(value.c_str(), value.size(), MPI_BYTE, r, DEFAULT_TAG, MPI_COMM_WORLD);
155 | 		}
156 | 
157 | 		/* Collect results from all other nodes. */
158 | 		for(int r=0; r<size; r++) {
159 | 			/* Root node is not included. */
160 | 			if(r == ROOT_NODE) {
161 | 				continue;
162 | 			}
163 | 
164 | 			GeneticAlgorithm ga;
165 | 			MPI_Recv(buffer, RECEIVE_BUFFER_SIZE, MPI_BYTE, r, DEFAULT_TAG, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
166 | 			ga.fromString(buffer);
167 | 			populations[r] = ga;
168 | 			if(ga.getBestFitness() < global.getBestFitness()) {
169 | 				global.setChromosome( ga.getBestChromosome() );
170 | 			}
171 | 			std::cout << "Worker " << r << " : " << ga.getBestChromosome().fitness << std::endl;
172 | 		}
173 | 
174 | 		std::cout << "Global : " << global.getBestChromosome().fitness << std::endl;
175 | 
176 | 
177 | 		counter++;
178 | 	} while(counter < NUMBER_OF_BROADCASTS);
179 | }
180 | 
181 | static void slave1() {
182 | 	unsigned long counter = 0;
183 | 
184 | 	if(rank == ROOT_NODE) {
185 | 		return;
186 | 	}
187 | 
188 | 	MPI_Recv(buffer, RECEIVE_BUFFER_SIZE, MPI_BYTE, ROOT_NODE, DEFAULT_TAG, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
189 | 	shuffled.fromString(buffer);
190 | 
191 | 	do {
192 | 		GeneticAlgorithm ga;
193 | 		MPI_Recv(buffer, RECEIVE_BUFFER_SIZE, MPI_BYTE, ROOT_NODE, DEFAULT_TAG, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
194 | 		ga.fromString(buffer);
195 | 
196 | 		/* Calculate as regular node. */
197 | 		GeneticAlgorithmOptimizer::optimize(ga, solved, shuffled, LOCAL_OPTIMIZATION_EPOCHES);
198 | 
199 | 		std::string result = ga.toString();
200 | 		MPI_Send(result.c_str(), result.size(), MPI_BYTE, ROOT_NODE, DEFAULT_TAG, MPI_COMM_WORLD);
201 | 
202 | 		counter++;
203 | 	} while(counter < NUMBER_OF_BROADCASTS);
204 | }
205 | 
206 | static void slave2() {
207 | 	slave1();
208 | }
209 | 
210 | int main(int argc, char **argv) {
211 | 	MPI_Init (&argc, &argv);
212 | 	MPI_Comm_rank(MPI_COMM_WORLD, &rank);
213 | 	MPI_Comm_size(MPI_COMM_WORLD, &size);
214 | 
215 | 	srand( time(NULL)^getpid() );
216 | 
217 | 	/* Firs process will distribute the working tasks. */
218 | 	shuffle();
219 | 
220 | 	solved.setDistanceType(HAUSDORFF);
221 | 	shuffled.setDistanceType(HAUSDORFF);
222 | 
223 | 	master1();
224 | 	slave1();
225 | 	master2();
226 | 	slave2();
227 | 
228 | 	solved.setDistanceType(EUCLIDEAN);
229 | 	shuffled.setDistanceType(EUCLIDEAN);
230 | 
231 | 	master1();
232 | 	slave1();
233 | 	master2();
234 | 	slave2();
235 | 
236 | 	MPI_Finalize();
237 | 
238 | 	return( EXIT_SUCCESS );
239 | }
240 | 


--------------------------------------------------------------------------------
/RubiksSide.h:
--------------------------------------------------------------------------------
 1 | #ifndef RUBIKSSIDE_H_INCLUDED
 2 | #define RUBIKSSIDE_H_INCLUDED
 3 | 
 4 | enum RubiksSide {
 5 | 	NONE = 'N',
 6 | 	TOP = 'T',
 7 | 	LEFT = 'L',
 8 | 	BACK = 'B',
 9 | 	RIGHT = 'R',
10 | 	FRONT = 'F',
11 | 	DOWN = 'D',
12 | };
13 | 
14 | #endif
15 | 


--------------------------------------------------------------------------------
/build.sh:
--------------------------------------------------------------------------------
1 | clear
2 | astyle "*.cpp" --indent=force-tab --style=java / -A2 --recursive
3 | astyle "*.c" --indent=force-tab --style=java / -A2 --recursive
4 | astyle "*.h" --indent=force-tab --style=java / -A2 --recursive
5 | find . -name "*.orig" -type f -delete
6 | rm RubiksCubeGA.exe
7 | mpicxx RubiksCubeGA.cpp -o RubiksCubeGA.exe
8 | nohup nice mpirun -np 8 ./RubiksCubeGA.exe $1
9 | 


--------------------------------------------------------------------------------
/selection.txt:
--------------------------------------------------------------------------------
 1 | #include <iostream>
 2 | 
 3 | using namespace std;
 4 | 
 5 | #define KEEP_ELITE true
 6 | 
 7 | 	int resultIndex = 0;
 8 | 	int firstIndex = 0;
 9 | 	int secondIndex = 0;
10 | 	int bestIndex = 0;
11 | 	int worstIndex = 0;
12 | 
13 |     int fitness[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
14 | 
15 |     unsigned long counters[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
16 | 
17 | 	void selectRandom() {
18 | 		do {
19 | 			resultIndex = rand() % 10;
20 | 			firstIndex = rand() % 10;
21 | 			secondIndex = rand() % 10;
22 | 		} while(resultIndex==firstIndex || resultIndex==secondIndex || (resultIndex == bestIndex && KEEP_ELITE==true));
23 | 	}
24 | 
25 | 	void selection() {
26 | 		static const int CROSSOVER_RESULT_INTO_BEST_PERCENT = 1;
27 | 		static const int CROSSOVER_RESULT_INTO_MIDDLE_PERCENT = 9;
28 | 		static const int CROSSOVER_RESULT_INTO_WORST_PERCENT = 90;
29 | 
30 | 		static int percent = -1;
31 | 		percent = rand()
32 | 				  % (CROSSOVER_RESULT_INTO_WORST_PERCENT
33 | 					 + CROSSOVER_RESULT_INTO_MIDDLE_PERCENT
34 | 					 + CROSSOVER_RESULT_INTO_BEST_PERCENT);
35 | 
36 | 		if (percent < CROSSOVER_RESULT_INTO_WORST_PERCENT) {
37 | 			do {
38 | 				selectRandom();
39 | 			} while (fitness[resultIndex] < fitness[firstIndex]
40 | 					 || fitness[resultIndex] < fitness[secondIndex]);
41 | 		} else if (percent
42 | 				   < (CROSSOVER_RESULT_INTO_WORST_PERCENT
43 | 					  + CROSSOVER_RESULT_INTO_MIDDLE_PERCENT)) {
44 | 			do {
45 | 				selectRandom();
46 | 			} while (fitness[resultIndex] < fitness[firstIndex]
47 | 					 || fitness[resultIndex] > fitness[secondIndex]);
48 | 		} else if (percent
49 | 				   < (CROSSOVER_RESULT_INTO_WORST_PERCENT
50 | 					  + CROSSOVER_RESULT_INTO_MIDDLE_PERCENT
51 | 					  + CROSSOVER_RESULT_INTO_BEST_PERCENT)) {
52 | 			do {
53 | 				selectRandom();
54 | 			} while (fitness[resultIndex] > fitness[firstIndex]
55 | 					 || fitness[resultIndex] > fitness[secondIndex]);
56 | 		}
57 | 	}
58 | 
59 | int main() {
60 |     unsigned long E = 10000000;
61 |     for(unsigned long e=0; e<E; e++){
62 |         selection();
63 |         counters[resultIndex]++;
64 |     }
65 | 
66 |     for(int i=0; i<10; i++){
67 |         cout << counters[i] << "\t" << 100*counters[i]/E << endl;
68 |     }
69 | 
70 | 	return 0;
71 | }
72 | 


--------------------------------------------------------------------------------