How to create the same random number in both c++ and Matlab?

I am currently using a written code in c++ that uses Mersenne Twister (mt19937) random number generator to generate the initial random solutions for an optimization algorithm. On the contrary, I have written my own code in Matlab environment for another optimization algorithm. Now, I want to compare the results of these two algorithms for different problems and for having a comparison, I need both algorithms to follow a specific seed number. In my Matlab code, I use the function rng(seed) to produce the same random solutions every time I run the program. Does anyone know how to change the code such that I can create the same initial solutions in both algorithms? It is worth mentioning that my seed in matlab is the average of two random integer numbers (74595103 and 82040812). Also, I attached The code of Mersenne Twister for more info. I would appreciate it if someone help me out in this regard.

#include <stdio.h>
#include "mt19937ar.h"

/* Period parameters */  
#define N 624
#define M 397
#define MATRIX_A 0x9908b0dfUL   /* constant vector a */
#define UPPER_MASK 0x80000000UL /* most significant w-r bits */
#define LOWER_MASK 0x7fffffffUL /* least significant r bits */

static unsigned long mt[N]; /* the array for the state vector  */
static int mti=N+1; /* mti==N+1 means mt[N] is not initialized */

void get_state(int* state_length, unsigned long** state, int** index) {
  *state_length = N;
  *state = mt;
  *index = &mti;
}

/* initializes mt[N] with a seed */
void init_genrand(unsigned long s)
{
    mt[0]= s & 0xffffffffUL;
    for (mti=1; mti<N; mti++) {
        mt[mti] = 
      (1812433253UL * (mt[mti-1] ^ (mt[mti-1] >> 30)) + mti); 
        /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */
        /* In the previous versions, MSBs of the seed affect   */
        /* only MSBs of the array mt[].                        */
        /* 2002/01/09 modified by Makoto Matsumoto             */
        mt[mti] &= 0xffffffffUL;
        /* for >32 bit machines */
    }
}

/* initialize by an array with array-length */
/* init_key is the array for initializing keys */
/* key_length is its length */
/* slight change for C++, 2004/2/26 */
void init_by_array(unsigned long init_key[], int key_length)
{
    int i, j, k;
    init_genrand(19650218UL);
    i=1; j=0;
    k = (N>key_length ? N : key_length);
    for (; k; k--) {
        mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL))
          + init_key[j] + j; /* non linear */
        mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
        i++; j++;
        if (i>=N) { mt[0] = mt[N-1]; i=1; }
        if (j>=key_length) j=0;
    }
    for (k=N-1; k; k--) {
        mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL))
          - i; /* non linear */
        mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */
        i++;
        if (i>=N) { mt[0] = mt[N-1]; i=1; }
    }

      mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ 
  }

/* generates a random number on [0,0xffffffff]-interval */
unsigned long genrand_int32(void)
{
    unsigned long y;
    static unsigned long mag01[2]={0x0UL, MATRIX_A};
    /* mag01[x] = x * MATRIX_A  for x=0,1 */

      if (mti >= N) { /* generate N words at one time */
          int kk;

          if (mti == N+1)   /* if init_genrand() has not been called, */
              init_genrand(5489UL); /* a default initial seed is used */

          for (kk=0;kk<N-M;kk++) {
              y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
              mt[kk] = mt[kk+M] ^ (y >> 1) ^ mag01[y & 0x1UL];
          }
          for (;kk<N-1;kk++) {
              y = (mt[kk]&UPPER_MASK)|(mt[kk+1]&LOWER_MASK);
              mt[kk] = mt[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1UL];
          }
          y = (mt[N-1]&UPPER_MASK)|(mt[0]&LOWER_MASK);
          mt[N-1] = mt[M-1] ^ (y >> 1) ^ mag01[y & 0x1UL];

          mti = 0;
      }

      y = mt[mti++];

      /* Tempering */
      y ^= (y >> 11);
      y ^= (y << 7) & 0x9d2c5680UL;
      y ^= (y << 15) & 0xefc60000UL;
      y ^= (y >> 18);

      return y;
  }

/* generates a random number on [0,0x7fffffff]-interval */
long genrand_int31(void)
{
    return (long)(genrand_int32()>>1);
}

/* generates a random number on [0,1]-real-interval */
double genrand_real1(void)
{
    return genrand_int32()*(1.0/4294967295.0); 
    /* divided by 2^32-1 */ 
}

/* generates a random number on [0,1)-real-interval */
double genrand_real2(void)
{
    return genrand_int32()*(1.0/4294967296.0); 
    /* divided by 2^32 */
}

/* generates a random number on (0,1)-real-interval */
double genrand_real3(void)
{
    return (((double)genrand_int32()) + 0.5)*(1.0/4294967296.0); 
    /* divided by 2^32 */
}

/* generates a random number on [0,1) with 53-bit resolution*/
double genrand_res53(void) 
{ 
    unsigned long a=genrand_int32()>>5, b=genrand_int32()>>6; 
    return(a*67108864.0+b)*(1.0/9007199254740992.0); 
} 
/* These real versions are due to Isaku Wada, 2002/01/09 added */

Answer 1

[Thorsten]

I would create a routine that writes the initial random numbers generated by the C code to a file and then read this file in Matlab. Or vice versa.