遗传算法C源代码示例：探索优化问题解法

/***************************************************************/ 
/* This is a simple genetic algorithm implementation where the */ 
/* evaluation function takes positive values only and the      */ 
/* fitness of an individual is the same as the value of the    */ 
/* objective function                                          */ 
/***************************************************************/ 

#include <stdio.h> 
#include <stdlib.h> 
#include <math.h> 

/* Change any of these parameters to match your needs */ 

#define POPSIZE 50               /* population size */ 
#define MAXGENS 1000             /* max. number of generations */ 
#define NVARS 3                  /* no. of problem variables */ 
#define PXOVER 0.8               /* probability of crossover */ 
#define PMUTATION 0.15           /* probability of mutation */ 
#define TRUE 1 
#define FALSE 0 

int generation;                  /* current generation no. */ 
int cur_best;                    /* best individual */ 
FILE *galog;                     /* an output file */ 

struct genotype /* genotype (GT), a member of the population */ 
{ 
 double gene[NVARS];        /* a string of variables */ 
 double fitness;            /* GT's fitness */ 
 double upper[NVARS];       /* GT's variables upper bound */ 

 double lower[NVARS];       /* GT's variables lower bound */ 
 double rfitness;           /* relative fitness */ 
 double cfitness;           /* cumulative fitness */ 
}; 

struct genotype population[POPSIZE+1];    /* population */ 
struct genotype newpopulation[POPSIZE+1]; /* new population; */ 
                                         /* replaces the */ 
                                         /* old generation */ 

/* Declaration of procedures used by this genetic algorithm */ 

void initialize(void); 
double randval(double, double); 
void evaluate(void); 
void keep_the_best(void); 
void elitist(void); 
void select(void); 
void crossover(void); 
void Xover(int,int); 
void swap(double *,double *); 
void mutate(void); 
void report(void); 

/***************************************************************/ 
/* Initialization function: Initializes the values of genes    */ 
/* within the variables bounds. It also initializes (to zero)  */ 
/* all fitness values for each member of the population. It    */ 
/* reads upper and lower bounds of each variable from the      */ 
/* input file `gadata.txt'. It randomly generates values       */