#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
#include <math.h>
#include <stdbool.h>
#define SIZE 9 // rozmiar planszy
#define BLOCK 3 // rozmiar bloku 3x3
// parametry GA
#define POP_SIZE 200 // liczebnosc populacji
#define MAX_GEN 5000 // maksymalna liczba generacji
#define TOURN_SIZE 3 // liczba w turnieju
#define CROSS_RATE 0.05 // prawdopodobienstwo krzyzowania
#define MUT_RATE 0.05 // prawdopodobienstwo mutacji
#define REPORT_GEN 50 // raport co
// dane sudoku, 0 = puste pole
int puzzle[ SIZE] [ SIZE] = {
{ 5 , 3 , 0 , 0 , 7 , 0 , 0 , 0 , 0 } ,
{ 6 , 0 , 0 , 1 , 9 , 5 , 0 , 0 , 0 } ,
{ 0 , 9 , 8 , 0 , 0 , 0 , 0 , 6 , 0 } ,
{ 8 , 0 , 0 , 0 , 6 , 0 , 0 , 0 , 3 } ,
{ 4 , 0 , 0 , 8 , 0 , 3 , 0 , 0 , 1 } ,
{ 7 , 0 , 0 , 0 , 2 , 0 , 0 , 0 , 6 } ,
{ 0 , 6 , 0 , 0 , 0 , 0 , 2 , 8 , 0 } ,
{ 0 , 0 , 0 , 4 , 1 , 9 , 0 , 0 , 5 } ,
{ 0 , 0 , 0 , 0 , 8 , 0 , 0 , 7 , 9 }
} ;
// struktura jednego osobnika
typedef struct {
int grid[ SIZE] [ SIZE] ; // wartosci w komorkach
int fitness; // ocena dopasowania
} Individual;
// deklaracje funkcji
void entry_individual( Individual * ind) ;
int evaluate_fitness( const Individual * ind) ;
Individual* tournament_selection( Individual pop[ ] ) ;
void crossover( const Individual * p1, const Individual * p2,
Individual * c1, Individual * c2, int generation) ;
void mutate( Individual * ind, int generation) ;
void do_sudoku_ga( void ) ;
void print_individual( const Individual * ind) ;
void print_iteration( int gen, const Individual * best) ;
// losowa liczba z przedzialu [a,b]
static int rand_range( int a, int b) {
return a
+ rand ( ) % ( b
- a
+ 1 ) ; }
// inicjalizacja osobnika: uzupelnienie pustych pol w blokach 3x3
void entry_individual( Individual * ind) {
bool fixed[ SIZE] [ SIZE] = { false } ;
// skopiuj stale wart
for ( int i = 0 ; i < SIZE; i++ ) {
for ( int j = 0 ; j < SIZE; j++ ) {
ind-> grid[ i] [ j] = puzzle[ i] [ j] ;
fixed[ i] [ j] = ( puzzle[ i] [ j] != 0 ) ;
}
}
// wypełnij kazdy blok
for ( int br = 0 ; br < BLOCK; br++ ) {
for ( int bc = 0 ; bc < BLOCK; bc++ ) {
bool present[ SIZE+ 1 ] = { false } ;
// zaznacz juz obecne wartosci
for ( int di = 0 ; di < BLOCK; di++ )
for ( int dj = 0 ; dj < BLOCK; dj++ ) {
int v = ind-> grid[ br* BLOCK+ di] [ bc* BLOCK+ dj] ;
if ( v) present[ v] = true ;
}
int missing[ SIZE] , m = 0 ;
// zbierz brakujace
for ( int v = 1 ; v <= SIZE; v++ )
if ( ! present[ v] ) missing[ m++ ] = v;
// losowo przemieszaj brakujace
for ( int x = m- 1 ; x > 0 ; x-- ) {
int tmp = missing[ x] ; missing[ x] = missing[ y] ; missing[ y] = tmp;
}
// wstaw w puste miejsca
int idx = 0 ;
for ( int di = 0 ; di < BLOCK; di++ )
for ( int dj = 0 ; dj < BLOCK; dj++ ) {
int r = br* BLOCK+ di, c = bc* BLOCK+ dj;
if ( ! fixed[ r] [ c] ) ind-> grid[ r] [ c] = missing[ idx++ ] ;
}
}
}
// oblicz fitness poczatkowy
ind-> fitness = evaluate_fitness( ind) ;
}
// ocena ile roznych liczb w kazdym wierszu i kolumnie
int evaluate_fitness( const Individual * ind) {
int score = 0 ;
int row_cnt[ SIZE+ 1 ] , col_cnt[ SIZE+ 1 ] ;
for ( int i = 0 ; i < SIZE; i++ ) {
memset ( row_cnt
, 0 , sizeof row_cnt
) ; memset ( col_cnt
, 0 , sizeof col_cnt
) ; for ( int j = 0 ; j < SIZE; j++ ) {
row_cnt[ ind-> grid[ i] [ j] ] ++;
col_cnt[ ind-> grid[ j] [ i] ] ++;
}
for ( int v = 1 ; v <= SIZE; v++ ) {
if ( row_cnt[ v] > 0 ) score++;
if ( col_cnt[ v] > 0 ) score++;
}
}
return score;
}
// selekcja turniejowa, najlepsze z TOURN_SIZE osobnikow
Individual* tournament_selection( Individual pop[ ] ) {
Individual * best = NULL;
for ( int i = 0 ; i < TOURN_SIZE; i++ ) {
Individual
* cand
= & pop
[ rand ( ) % POP_SIZE
] ; if ( ! best || cand-> fitness > best-> fitness) best = cand;
}
return best;
}
// krzyzowanie swapuj losowo bloki 3x3 z CROSS_RATE %
void crossover( const Individual * p1, const Individual * p2,
Individual * c1, Individual * c2, int generation) {
// skopiuj rodzicow
memcpy ( c1
-> grid
, p1
-> grid
, sizeof p1
-> grid
) ; memcpy ( c2
-> grid
, p2
-> grid
, sizeof p2
-> grid
) ; if ( ( double ) rand ( ) / RAND_MAX
< CROSS_RATE
) { for ( int br = 0 ; br < BLOCK; br++ ) {
for ( int bc = 0 ; bc < BLOCK; bc++ ) {
// zamien blok
for ( int di = 0 ; di < BLOCK; di++ )
for ( int dj = 0 ; dj < BLOCK; dj++ ) {
int r = br* BLOCK+ di, c = bc* BLOCK+ dj;
int tmp = c1-> grid[ r] [ c] ;
c1-> grid[ r] [ c] = c2-> grid[ r] [ c] ;
c2-> grid[ r] [ c] = tmp;
}
}
}
}
}
c1-> fitness = evaluate_fitness( c1) ;
c2-> fitness = evaluate_fitness( c2) ;
}
// mutacja = w jednym bloku zamienia dwie losowe puste komorki
void mutate( Individual * ind, int generation) {
if ( ( double ) rand ( ) / RAND_MAX
>= MUT_RATE
) return ; int br = rand_range( 0 , BLOCK- 1 ) , bc = rand_range( 0 , BLOCK- 1 ) ;
int idxs[ SIZE] , m = 0 ;
for ( int di = 0 ; di < BLOCK; di++ )
for ( int dj = 0 ; dj < BLOCK; dj++ ) {
int r = br* BLOCK+ di, c = bc* BLOCK+ dj;
if ( puzzle[ r] [ c] == 0 ) idxs[ m++ ] = r* SIZE + c;
}
if ( m < 2 ) return ;
int a
= idxs
[ rand ( ) % m
] , b
= idxs
[ rand ( ) % m
] ; if ( a != b) {
int r1 = a/ SIZE, c1 = a% SIZE;
int r2 = b/ SIZE, c2 = b% SIZE;
int tmp = ind-> grid[ r1] [ c1] ;
ind-> grid[ r1] [ c1] = ind-> grid[ r2] [ c2] ;
ind-> grid[ r2] [ c2] = tmp;
ind-> fitness = evaluate_fitness( ind) ;
}
}
// glowna petla
void do_sudoku_ga( void ) {
Individual pop[ POP_SIZE] , newpop[ POP_SIZE] ;
// inicjalizacja populacji
for ( int i = 0 ; i < POP_SIZE; i++ ) entry_individual( & pop[ i] ) ;
Individual best = pop[ 0 ] ;
for ( int gen = 1 ; gen <= MAX_GEN; gen++ ) {
// aktualizacja najlepszego
for ( int i = 0 ; i < POP_SIZE; i++ )
if ( pop[ i] .fitness > best.fitness ) best = pop[ i] ;
// raport co mniej jesli wystarczy
if ( gen % REPORT_GEN == 0 ) print_iteration( gen, & best) ;
// tworzenie nastepnej populacji
for ( int i = 0 ; i < POP_SIZE; i += 2 ) {
Individual * p1 = tournament_selection( pop) ;
Individual * p2 = tournament_selection( pop) ;
crossover( p1, p2, & newpop[ i] , & newpop[ i+ 1 ] , gen) ;
mutate( & newpop[ i] , gen) ;
mutate( & newpop[ i+ 1 ] , gen) ;
}
memcpy ( pop
, newpop
, sizeof pop
) ; // znaleziono idealne rozwiazanie
if ( best.fitness == 2 * SIZE * SIZE) break ;
}
// wynik
printf ( "\n Final best fitness %d/%d\n " , best.
fitness , 2 * SIZE
* SIZE
) ; print_individual( & best) ;
}
// wyswietlenie
void print_individual( const Individual * ind) {
for ( int i = 0 ; i < SIZE; i++ ) {
for ( int j = 0 ; j < SIZE; j++ )
printf ( "%d " , ind
-> grid
[ i
] [ j
] ) ; }
}
// raport
void print_iteration( int gen, const Individual * best) {
printf ( "Gen %4d, best fitness=%3d\n " , gen
, best
-> fitness
) ; }
int main( void ) {
do_sudoku_ga( ) ;
return 0 ;
}
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
#include <math.h>
#include <stdbool.h>

#define SIZE        9      // rozmiar planszy
#define BLOCK       3      // rozmiar bloku 3x3

// parametry GA
#define POP_SIZE    200    // liczebnosc populacji
#define MAX_GEN     5000   // maksymalna liczba generacji
#define TOURN_SIZE  3      // liczba w turnieju
#define CROSS_RATE  0.05    // prawdopodobienstwo krzyzowania
#define MUT_RATE    0.05    // prawdopodobienstwo mutacji

#define REPORT_GEN 50      // raport co

// dane sudoku, 0 = puste pole
int puzzle[SIZE][SIZE] = {
    {5,3,0, 0,7,0, 0,0,0},
    {6,0,0, 1,9,5, 0,0,0},
    {0,9,8, 0,0,0, 0,6,0},

    {8,0,0, 0,6,0, 0,0,3},
    {4,0,0, 8,0,3, 0,0,1},
    {7,0,0, 0,2,0, 0,0,6},

    {0,6,0, 0,0,0, 2,8,0},
    {0,0,0, 4,1,9, 0,0,5},
    {0,0,0, 0,8,0, 0,7,9}
};

// struktura jednego osobnika
typedef struct {
    int grid[SIZE][SIZE]; // wartosci w komorkach
    int fitness;          // ocena dopasowania
} Individual;

// deklaracje funkcji
void entry_individual(Individual *ind);
int  evaluate_fitness(const Individual *ind);
Individual* tournament_selection(Individual pop[]);
void crossover(const Individual *p1, const Individual *p2,
               Individual *c1, Individual *c2, int generation);
void mutate(Individual *ind, int generation);
void do_sudoku_ga(void);
void print_individual(const Individual *ind);
void print_iteration(int gen, const Individual *best);

// losowa liczba z przedzialu [a,b]
static int rand_range(int a, int b) {
    return a + rand() % (b - a + 1);
}

// inicjalizacja osobnika: uzupelnienie pustych pol w blokach 3x3
void entry_individual(Individual *ind) {
    bool fixed[SIZE][SIZE] = {false};
    // skopiuj stale wart
    for (int i = 0; i < SIZE; i++) {
        for (int j = 0; j < SIZE; j++) {
            ind->grid[i][j] = puzzle[i][j];
            fixed[i][j] = (puzzle[i][j] != 0);
        }
    }
    // wypełnij kazdy blok
    for (int br = 0; br < BLOCK; br++) {
        for (int bc = 0; bc < BLOCK; bc++) {
            bool present[SIZE+1] = {false};
            // zaznacz juz obecne wartosci
            for (int di = 0; di < BLOCK; di++)
            for (int dj = 0; dj < BLOCK; dj++) {
                int v = ind->grid[br*BLOCK+di][bc*BLOCK+dj];
                if (v) present[v] = true;
            }
            int missing[SIZE], m = 0;
            // zbierz brakujace
            for (int v = 1; v <= SIZE; v++)
                if (!present[v]) missing[m++] = v;
            // losowo przemieszaj brakujace
            for (int x = m-1; x > 0; x--) {
                int y = rand() % (x+1);
                int tmp = missing[x]; missing[x] = missing[y]; missing[y] = tmp;
            }
            // wstaw w puste miejsca
            int idx = 0;
            for (int di = 0; di < BLOCK; di++)
            for (int dj = 0; dj < BLOCK; dj++) {
                int r = br*BLOCK+di, c = bc*BLOCK+dj;
                if (!fixed[r][c]) ind->grid[r][c] = missing[idx++];
            }
        }
    }
    // oblicz fitness poczatkowy
    ind->fitness = evaluate_fitness(ind);
}

// ocena ile roznych liczb w kazdym wierszu i kolumnie
int evaluate_fitness(const Individual *ind) {
    int score = 0;
    int row_cnt[SIZE+1], col_cnt[SIZE+1];
    for (int i = 0; i < SIZE; i++) {
        memset(row_cnt, 0, sizeof row_cnt);
        memset(col_cnt, 0, sizeof col_cnt);
        for (int j = 0; j < SIZE; j++) {
            row_cnt[ind->grid[i][j]]++;
            col_cnt[ind->grid[j][i]]++;
        }
        for (int v = 1; v <= SIZE; v++) {
            if (row_cnt[v] > 0) score++;
            if (col_cnt[v] > 0) score++;
        }
    }
    return score;
}

// selekcja turniejowa, najlepsze z TOURN_SIZE osobnikow
Individual* tournament_selection(Individual pop[]) {
    Individual *best = NULL;
    for (int i = 0; i < TOURN_SIZE; i++) {
        Individual *cand = &pop[rand() % POP_SIZE];
        if (!best || cand->fitness > best->fitness) best = cand;
    }
    return best;
}

// krzyzowanie swapuj losowo bloki 3x3 z CROSS_RATE %
void crossover(const Individual *p1, const Individual *p2,
               Individual *c1, Individual *c2, int generation) {
    // skopiuj rodzicow
    memcpy(c1->grid, p1->grid, sizeof p1->grid);
    memcpy(c2->grid, p2->grid, sizeof p2->grid);
    if ((double)rand()/RAND_MAX < CROSS_RATE) {
        for (int br = 0; br < BLOCK; br++) {
            for (int bc = 0; bc < BLOCK; bc++) {
                if (rand()%2) {
                    // zamien blok
                    for (int di = 0; di < BLOCK; di++)
                    for (int dj = 0; dj < BLOCK; dj++) {
                        int r = br*BLOCK+di, c = bc*BLOCK+dj;
                        int tmp = c1->grid[r][c];
                        c1->grid[r][c] = c2->grid[r][c];
                        c2->grid[r][c] = tmp;
                    }
                }
            }
        }
    }
    c1->fitness = evaluate_fitness(c1);
    c2->fitness = evaluate_fitness(c2);
}

// mutacja = w jednym bloku zamienia dwie losowe puste komorki
void mutate(Individual *ind, int generation) {
    if ((double)rand()/RAND_MAX >= MUT_RATE) return;
    int br = rand_range(0, BLOCK-1), bc = rand_range(0, BLOCK-1);
    int idxs[SIZE], m = 0;
    for (int di = 0; di < BLOCK; di++)
    for (int dj = 0; dj < BLOCK; dj++) {
        int r = br*BLOCK+di, c = bc*BLOCK+dj;
        if (puzzle[r][c] == 0) idxs[m++] = r*SIZE + c;
    }
    if (m < 2) return;
    int a = idxs[rand()%m], b = idxs[rand()%m];
    if (a != b) {
        int r1 = a/SIZE, c1 = a%SIZE;
        int r2 = b/SIZE, c2 = b%SIZE;
        int tmp = ind->grid[r1][c1];
        ind->grid[r1][c1] = ind->grid[r2][c2];
        ind->grid[r2][c2] = tmp;
        ind->fitness = evaluate_fitness(ind);
    }
}

// glowna petla
void do_sudoku_ga(void) {
    srand((unsigned)time(NULL));
    Individual pop[POP_SIZE], newpop[POP_SIZE];
    // inicjalizacja populacji
    for (int i = 0; i < POP_SIZE; i++) entry_individual(&pop[i]);
    Individual best = pop[0];

    for (int gen = 1; gen <= MAX_GEN; gen++) {
        // aktualizacja najlepszego
        for (int i = 0; i < POP_SIZE; i++)
            if (pop[i].fitness > best.fitness) best = pop[i];
        // raport co mniej jesli wystarczy
        if (gen % REPORT_GEN == 0) print_iteration(gen, &best);
        // tworzenie nastepnej populacji
        for (int i = 0; i < POP_SIZE; i += 2) {
            Individual *p1 = tournament_selection(pop);
            Individual *p2 = tournament_selection(pop);
            crossover(p1, p2, &newpop[i], &newpop[i+1], gen);
            mutate(&newpop[i],   gen);
            mutate(&newpop[i+1], gen);
        }
        memcpy(pop, newpop, sizeof pop);
        // znaleziono idealne rozwiazanie
        if (best.fitness == 2 * SIZE * SIZE) break;
    }
    // wynik
    printf("\nFinal best fitness %d/%d\n", best.fitness, 2*SIZE*SIZE);
    print_individual(&best);
}

// wyswietlenie
void print_individual(const Individual *ind) {
    for (int i = 0; i < SIZE; i++) {
        for (int j = 0; j < SIZE; j++)
            printf("%d ", ind->grid[i][j]);
        printf("\n");
    }
}

// raport
void print_iteration(int gen, const Individual *best) {
    printf("Gen %4d, best fitness=%3d\n", gen, best->fitness);
}

int main(void) {
    printf("GA Sudoku solver\n");
    do_sudoku_ga();
    return 0;
}
stdout
GA Sudoku solver
Gen 50, best fitness=147
Gen 100, best fitness=150
Gen 150, best fitness=151
Gen 200, best fitness=151
Gen 250, best fitness=151
Gen 300, best fitness=151
Gen 350, best fitness=153
Gen 400, best fitness=154
Gen 450, best fitness=156
Gen 500, best fitness=156
Gen 550, best fitness=156
Gen 600, best fitness=156
Gen 650, best fitness=156
Gen 700, best fitness=156
Gen 750, best fitness=156
Gen 800, best fitness=156
Gen 850, best fitness=156
Gen 900, best fitness=156
Gen 950, best fitness=156
Gen 1000, best fitness=156
Gen 1050, best fitness=156
Gen 1100, best fitness=156
Gen 1150, best fitness=156
Gen 1200, best fitness=156
Gen 1250, best fitness=156
Gen 1300, best fitness=156
Gen 1350, best fitness=156
Gen 1400, best fitness=156
Gen 1450, best fitness=156
Gen 1500, best fitness=156
Gen 1550, best fitness=156
Gen 1600, best fitness=156
Gen 1650, best fitness=156
Gen 1700, best fitness=156
Gen 1750, best fitness=156
Gen 1800, best fitness=156
Gen 1850, best fitness=156
Gen 1900, best fitness=158
Gen 1950, best fitness=158
Gen 2000, best fitness=158
Gen 2050, best fitness=160
Gen 2100, best fitness=160
Gen 2150, best fitness=160
Gen 2200, best fitness=160
Gen 2250, best fitness=160
Gen 2300, best fitness=160
Gen 2350, best fitness=160
Gen 2400, best fitness=160
Gen 2450, best fitness=160
Gen 2500, best fitness=160
Gen 2550, best fitness=160
Gen 2600, best fitness=160
Gen 2650, best fitness=160
Gen 2700, best fitness=160
Gen 2750, best fitness=160
Gen 2800, best fitness=160
Gen 2850, best fitness=160
Gen 2900, best fitness=160
Gen 2950, best fitness=160
Gen 3000, best fitness=160
Gen 3050, best fitness=160
Gen 3100, best fitness=160
Gen 3150, best fitness=160
Gen 3200, best fitness=160
Gen 3250, best fitness=160
Gen 3300, best fitness=160
Gen 3350, best fitness=160
Gen 3400, best fitness=160
Gen 3450, best fitness=160
Gen 3500, best fitness=160
Gen 3550, best fitness=160
Gen 3600, best fitness=160
Gen 3650, best fitness=160
Gen 3700, best fitness=160
Gen 3750, best fitness=160
Gen 3800, best fitness=160
Gen 3850, best fitness=160
Gen 3900, best fitness=160
Gen 3950, best fitness=160
Gen 4000, best fitness=160
Gen 4050, best fitness=160
Gen 4100, best fitness=160
Gen 4150, best fitness=160
Gen 4200, best fitness=160
Gen 4250, best fitness=160
Gen 4300, best fitness=160
Gen 4350, best fitness=160
Gen 4400, best fitness=160
Gen 4450, best fitness=160
Gen 4500, best fitness=160
Gen 4550, best fitness=160
Gen 4600, best fitness=160
Gen 4650, best fitness=160
Gen 4700, best fitness=160
Gen 4750, best fitness=160
Gen 4800, best fitness=160
Gen 4850, best fitness=160
Gen 4900, best fitness=160
Gen 4950, best fitness=160
Final best fitness 162/162
5 3 4 6 7 8 9 1 2
6 7 2 1 9 5 3 4 8
1 9 8 3 4 2 5 6 7
8 5 9 7 6 1 4 2 3
4 2 6 8 5 3 7 9 1
7 1 3 9 2 4 8 5 6
9 6 1 5 3 7 2 8 4
2 8 7 4 1 9 6 3 5
3 4 5 2 8 6 1 7 9