差分進化アルゴリズムC言語実装

以前の1篇の中で自分の大学院生の期間C実現の基本粒子群のアルゴリズムを貼って、実行速度は明らかに他の高級言語より速くて、これも各プログラミング言語の間の違いで、今かつて輝かしい差分進化のアルゴリズムに対してC言語の実現を行います.変異戦略はDE/rand/1を採用しており,これは最も一般的である.間違ったところがあればどうぞ.

/***************Differential Evolution Algorithm*************************/
/*
* @Author: Gong Xu
* (c) Copyright 2018 ，DSP Laboratory of Lanzhou University of Technology, All rights reserved. 
*
*/

# include
# include
# include
#include 
#define nVar 30  // Number of variables
#define nPop 50   // Number of Population
#define Iter 1000  // Maximum number of iterations

struct individual
{
	double position[nVar];
	double fitness;

};

struct DE
{
	struct individual ptcle[nPop];
	double F;
	double CR;
	double(*function)(double *);  // Function pointer definition
	double global_fitness;
	double global_solution[nVar];
	double x_low_bound;
	double x_up_bound;


};
// sum(X^2)
double function_fitness(double *var)
{
	double result = 0;
	for (int i = 0; i de.x_up_bound)
				{
					mutate[i].position[j] = de.x_up_bound;
				}
				if (mutate[i].position[j] < de.x_low_bound)
				{
					mutate[i].position[j] = de.x_low_bound;
				}
			}
		 }
		
		//crossover
		for (int i = 0; i < nPop; i++)
		{

			int randc = (int)rand() % nVar;
			for (int j = 0; j < nVar; j++)
			{
				double rand_cr = (double)rand() / RAND_MAX;
				if ((j == randc) || (rand_cr < de.CR))
				{
					cross[i].position[j] = mutate[i].position[j];
				}
				else
				{
					cross[i].position[j] = de.ptcle[i].position[j];
				}
				// limit of variables of bound
				if (cross[i].position[j] > de.x_up_bound)
				{
					cross[i].position[j] = de.x_up_bound;
				}
				if (cross[i].position[j] < de.x_low_bound)
				{
					cross[i].position[j] = de.x_low_bound;
				}
			}
			
			cross[i].fitness = de.function(cross[i].position);
		}
		// select
		for (int i = 0; i < nPop; i++)
		{
			if (cross[i].fitness < de.ptcle[i].fitness)
			{
				de.ptcle[i].fitness = cross[i].fitness;
				memcpy(&de.ptcle[i].position, &cross[i].position, sizeof(double)*nVar);
				
				if (de.ptcle[i].fitness