EDBF优化算法来源：Zuo, Z., Yan, L., Ullah, S., Sun, Y., Zhang, R., & Zhao, H. (2021). Empirical distribution-based framework for improving multi-parent crossover algorithms. Soft Computing, 1-24.
编译器：VS2015
1. 新建一个dll工程（工程名：EDBFDLL.cpp）
文件----新建-----项目-----模板-----Win32-----Win32项目------应用程序设置------应用程序类型------DLL
项目名称（右键）-----添加-----类------类名与dll工程名一致（EDBFDLL.h）
2.EDBFDLL.h代码：
1 #ifndef EDBFDLL_H
2 #define EDBFDLL_H
3 #pragma once
4 #define LD double
5 #define PI 3.141592654
6 #define Euler 2.71828182845904523536
7 #include "stdafx.h"
8 #include <time.h>
9 #include <stdlib.h>
10 #include <stdio.h>
11 #include <math.h>
12 #include <iostream>
13 #include <iomanip>
14 #include <time.h>
15 #include <fstream>
16 #include <sstream>
17 using namespace std;
18
19 class _declspec(dllexport) EDBFDLL
20 {
21 private:
22 LD Random();
23 double loge(double x);
24 void OutputScreen(int iterationNum, LD duration);
25 void OpenSpace(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum);
26
27 public:
28 EDBFDLL();
29 ~EDBFDLL();
30 struct B
31 {
32 LD * p;
33 LD f;
34 };
35 LD * a = NULL;
36 B * x = NULL, *new_x = NULL, *new_l_x = NULL;
37 void f(B & x, int n);
38 void f_array(int N, int n, B *&x);
39 int H(B x, int n, LD * GenesLeftLim, LD * GenesRightLim);
40 bool better(B x1, B x2, int n, LD * GenesLeftLim, LD * GenesRightLim);
41 void rand_init_population(int N, int n, B * _x, LD * GenesLeftLim, LD * GenesRightLim);
42 void swap(B &a, B &b);
43 void sort(int N, int n, B * x);
44 void rd(int M);
45 void mrd(int M);
46 void ConstraintLaw(int M);
47 void e_m_p_c(int M, int K, int L, int n, int N, B * _x);
48 void H(int n, int N, int M, int K, int L, B * _x, LD * GenesLeftLim, LD * GenesRightLim);
49 int Recombination(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum, int ElitistParentChromosomesNum, LD * GenesLeftLim, LD * GenesRightLim);
50 clock_t Encoding(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum, int ElitistParentChromosomesNum, LD * GenesLeftLim, LD * GenesRightLim);
51 EDBFDLL::B ED_BF(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum, int ElitistParentChromosomesNum, LD * GenesLeftLim, LD * GenesRightLim);
52 void DeleteSpace();
53 void Write_to_excel(B * _x, int p, int n, ofstream & outfile);
54 };
55 #endif
展开代码
3.EDBFDLL.cpp代码
1 // EDBFDLL.cpp : 定义 DLL 应用程序的导出函数。
2 //
3
4 #include "stdafx.h"
5 #include "EDBFDLL.h"
6
7 EDBFDLL::EDBFDLL()
8 {
9 }
10
11
12 EDBFDLL::~EDBFDLL()
13 {
14 }
15
16 LD EDBFDLL::Random()
17 {
18 return (LD)rand() / RAND_MAX;
19 }
20 double EDBFDLL::loge(double x)
21 {
22 return log(x) / log(exp(1));
23 }
24 //fitness function
25 void EDBFDLL::f(B & x, int n)//n present dimension
26 {
27 /*f1*/
28 /*double val1 = 0;
29 double val2 = 0;
30 for (int i = 0; i < n; i++) {
31 val1 += x.p[i] * x.p[i];
32 val2 += cos(2 * PI*x.p[i] / 180 * PI);
33 }
34 x.f = ((-20)*exp((-0.2)*sqrt(val1 / n)) - exp(val2 / n) + 20 + exp(1));*/
35 /*f2*/
36 //double val = 0;
37 //for (int i = 0; i < n; i++)
38 // val += (x.p[i] * x.p[i]);
39 //x.f=-exp(-0.5*val);
40 /*f3*/
41 //LD a, s = 0;
42 //for (int i = 0; i<n; i++)
43 //{
44 // a = x.p[i] * x.p[i] - 10 * cos(2 * PI*x.p[i]);
45 // s += a;
46 //}
47 //x.f = s + 10 * n;
48 /*f4*/
49 //double val = 0;
50 //for (int i = 0; i < n; i++)
51 // val += x.p[i] * sin(sqrt(abs(x.p[i])));
52 //x.f=-val;
53 /*f5*/
54 /*double val1 = 0, val2 = 1;
55 for (int i = 0; i < n; i++)
56 val1 += (loge(x.p[i] - 2)*loge(x.p[i] - 2) + loge(10 - x.p[i])*loge(10 - x.p[i]));
57 for (int i = 0; i < 10; i++)
58 val2 *= x.p[i];
59 x.f=val1 - pow(val2, 0.2);*/
60 /*f6*/
61 /*double val = 0;
62 for (int i = 0; i < n; i++) {
63 val += x.p[i] * x.p[i];
64 }
65 x.f=val;*/
66 /*f7*/
67 double val = 0;
68 for (int i = 0; i < n - 1; i++) {
69 val += 100 * (x.p[i + 1] - x.p[i] * x.p[i])*(x.p[i + 1] - x.p[i] * x.p[i]) + (x.p[i] - 1)*(x.p[i] - 1);
70 }
71 x.f = val;
72 /*f8*/
73 //double val = 0;
74 //for (int i = 0; i < n; i++)
75 // val += (x.p[i] - i - 1)*(x.p[i] - i - 1);
76 //x.f = val;
77 /*f9*/
78 //double val1 = 0;
79 //double val2 = 1;
80 //for (int i = 0; i < n; i++) {
81 // val1 += abs(x.p[i]);
82 // val2 = val2*abs(x.p[i]);
83 //}
84 //x.f=(val1 + val2);
85 /*f10*/
86 //double val = 0;
87 //for (int i = 0; i < n; i++)
88 // val += (i + 1)*x.p[i] * x.p[i];
89 //x.f = val;
90 }
91 //返回一组适应值
92 void EDBFDLL::f_array(int N, int n, B *&x)
93 {
94 for (int i = 0; i<N; i++)
95 {
96 f(x[i], n);
97 }
98 }
99
100 //若满足约束条件，返回true，否则，返回false
101 int EDBFDLL::H(B x, int n, LD * GenesLeftLim, LD * GenesRightLim)
102 {
103 int i, s = 0;
104 for (i = 0; i<n; i++)
105 {
106 if (x.p[i] >= GenesLeftLim[i])
107 s += 1;
108 if (x.p[i] <= GenesRightLim[i])
109 s += 1;
110 }
111 return s;
112 }
113 bool EDBFDLL::better(B x1, B x2, int n, LD * GenesLeftLim, LD * GenesRightLim)
114 {
115 int h1, h2;
116 LD f1, f2;
117 h1 = H(x1, n, GenesLeftLim, GenesRightLim);
118 h2 = H(x2, n, GenesRightLim, GenesRightLim);
119 f1 = x1.f;
120 f2 = x2.f;
121 if (h1<h2)
122 return false;
123 else if (h1>h2)
124 return true;
125 if (f1<f2)
126 return true;
127 return false;
128 }
129 //返回在搜索空间中随机产生满足约束条件的初始群体,t=0
130 void EDBFDLL::rand_init_population(int N, int n, B * _x, LD * GenesLeftLim, LD * GenesRightLim)//N presents the population size, n peresents the dimension
131 {
132 int i, j;
133 for (i = 0; i<N; ++i)
134 {
135 for (j = 0; j<n; j++)
136 {
137 _x[i].p[j] = Random()*(GenesRightLim[j] - GenesLeftLim[j]) + GenesLeftLim[j];
138 }
139 }
140 }
141 void EDBFDLL::swap(B &a, B &b)
142 {
143 B temp = a;
144 a = b;
145 b = temp;
146 }
147 void EDBFDLL::sort(int N, int n, B * x)
148 {
149 for (int i = 0; i<N - 1; i++)
150 {
151 for (int j = 0; j<N - 1 - i; j++)
152 {
153 if (x[j].f>x[j + 1].f)
154 {
155 swap(x[j], x[j + 1]);
156 }
157 }
158 }
159 }
160 void EDBFDLL::rd(int M)
161 {
162 LD s, g = 4;
163 while (g>1.5 || g<-0.5)
164 {
165 s = 0;
166 for (int i = 0; i<M - 1; i++)
167 {
168 a[i] = Random() * 2 - 0.5;
169 s += a[i];
170 }
171 g = 1 - s;
172 }
173 a[M - 1] = g;
174 }
175 //从[-0.5,1.5]中随机产生M个数,使得这M个数和为1
176 void EDBFDLL::mrd(int M)
177 {
178 LD s1 = -0.8586*powf(M, -0.9424) + 0.6115;
179 LD s2 = 0.5802*powf(M, -0.8598) + 0.3443;
180 int i;
181 LD s, g = 4, fld;
182 while (g>1.5 || g<-0.5)
183 {
184 s = 0;
185 for (i = 0; i<M - 1; i++)
186 {
187 fld = Random();
188 if (fld <= s1)
189 a[i] = Random()*0.5 - 0.5;
190 else if (fld <= s1 + s2)
191 a[i] = Random();
192 else
193 a[i] = Random()*0.5 + 1;
194 s += a[i];
195 }
196 g = 1 - s;
197 }
198 a[M - 1] = g;
199 }
200 void EDBFDLL::ConstraintLaw(int M)
201 {
202 LD s, S, Last_Coeffient = 2, num = 0, t_low, t_up, b_low, b_up;
203 int r;
204 a[0] = Random() * 2 - 0.5;
205
206 while (Last_Coeffient <= -0.5 || Last_Coeffient >= 1.5)
207 {
208 num++;
209 S = s = 0;
210 for (int i = 1; i < M - 1; i++)
211 {
212 s += a[i - 1];
213 t_low = -0.5 - s;
214 t_up = 1.5 - s;
215 b_low = t_low >= -0.5 ? t_low : -0.5;
216 b_up = t_up <= 1.5 ? t_up : 1.5;
217 a[i] = Random()*(b_up - b_low) + b_low;
218 }
219 S = s + a[M - 2];
220 a[M - 1] = Last_Coeffient = 1 - S;
221 }
222 }
223 //精英多父体杂交
224 void EDBFDLL::e_m_p_c(int M, int K, int L, int n, int N, B * _x)
225 {
226 int i, j, l;
227 LD S;
228
229 //从种群中选择K个最好的个体
230 for (i = 0; i<K; i++)
231 {
232 new_x[i] = _x[i];
233 }
234 //另外M-K个个体从种群中随机选取
235 for (i = 0; i<M - K; i++)
236 {
237 int t = rand() % N;
238 while (t<K)
239 {
240 t = rand() % N;
241 }
242 new_x[i + K] = _x[t];
243 }
244 //由这M个个体张成子空间
245 for (l = 0; l<L; l++)
246 {
247 mrd(M);
248 //ConstraintLaw(M);
249 for (i = 0; i<n; i++)
250 {
251 S = 0;
252 for (j = 0; j<M; j++)
253 {
254 S += new_x[j].p[i] * a[j];
255 }
256 new_l_x[l].p[i] = S;
257 }
258 }
259 //返回L个个体中最好的个体
260 f_array(L, n, new_l_x);
261 sort(L, n, new_l_x);
262 }
263 //每执行一次H函数，就为一代
264 void EDBFDLL::H(int n, int N, int M, int K, int L, B * _x, LD * GenesLeftLim, LD * GenesRightLim)
265 {
266 B best, worst;
267 worst = _x[N - 1];
268 e_m_p_c(M, K, L, n, N, _x);
269 best = new_l_x[0];
270 if (better(best, worst, n, GenesLeftLim, GenesRightLim))
271 {
272 for (int i = 0; i<n; i++)
273 {
274 _x[N - 1].p[i] = best.p[i];
275 }
276 _x[N - 1].f = best.f;
277 }
278 sort(N, n, _x);
279 }
280 void EDBFDLL::Write_to_excel(B * _x, int p, int n, ofstream & outfile)
281 {
282
283 for (int i = 0; i<p; i++)
284 {
285 for (int j = 0; j<n; j++)
286 outfile << setiosflags(ios::fixed) << setprecision(14) << _x[i].p[j] << ",";
287 outfile << _x[i].f << endl;
288 }
289
290 }
291 void EDBFDLL::OpenSpace(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum)
292 {
293 int i;
294 try
295 {
296 a = new LD[ParentChromosomesNum];
297 x = new B[PullChromosomesNum];
298 new_x = new B[ParentChromosomesNum];
299 new_l_x = new B[1];
300 }
301 catch (bad_alloc&memExp)
302 {
303 cerr << memExp.what() << endl;
304 }
305 try
306 {
307 for (i = 0; i<PullChromosomesNum; i++)
308 {
309 x[i].p = new LD[GenesNum];
310 }
311 for (i = 0; i<ParentChromosomesNum; i++)
312 {
313 new_x[i].p = new LD[GenesNum];
314 }
315 for (i = 0; i<1; i++)
316 {
317 new_l_x[i].p = new LD[GenesNum];
318 }
319 }
320 catch (bad_alloc&memExp)
321 {
322 cerr << memExp.what() << endl;
323 }
324 }
325 int EDBFDLL::Recombination(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum, int ElitistParentChromosomesNum, LD * GenesLeftLim, LD * GenesRightLim)
326 {
327 ofstream outfile;
328 outfile.open("result.csv", ios::out);
329 int i = 0;
330 while (fabs(x[0].f - x[PullChromosomesNum - 1].f)>1E-14)//fabs(x[0].f-x[N-1].f)>1E-14
331 {
332 ++i;
333 H(GenesNum, PullChromosomesNum, ParentChromosomesNum, ElitistParentChromosomesNum, 1, x, GenesLeftLim, GenesRightLim);
334 outfile << setiosflags(ios::fixed) << setprecision(14) << x[0].f << endl;
335 }
336 outfile.close();
337 return i;
338 }
339 clock_t EDBFDLL::Encoding(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum, int ElitistParentChromosomesNum, LD * GenesLeftLim, LD * GenesRightLim)
340 {
341 clock_t start = clock();
342 srand((unsigned)time(NULL));
343 OpenSpace(ParentChromosomesNum, GenesNum, PullChromosomesNum);
344 rand_init_population(PullChromosomesNum, GenesNum, x, GenesLeftLim, GenesRightLim);
345 f_array(PullChromosomesNum, GenesNum, x);
346 sort(PullChromosomesNum, GenesNum, x);
347 return start;
348 }
349 void EDBFDLL::OutputScreen(int iterationNum, LD duration)
350 {
351 cout << "程序执行代数:" << iterationNum << "代" << endl;//hj
352 cout << "程序运行时间:" << setiosflags(ios::fixed) << setprecision(4) << duration << "s" << endl;
353 cout << "程序运行结果:" << setiosflags(ios::fixed) << setprecision(16) << x[0].f << endl;
354 }
355 void EDBFDLL::DeleteSpace()
356 {
357 delete[] a; a = NULL;
358 delete[] x; x = NULL;
359 delete[] new_x; new_x = NULL;
360 delete[] new_l_x; new_l_x = NULL;
361 }
362 EDBFDLL::B EDBFDLL::ED_BF(int ParentChromosomesNum, int GenesNum, int PullChromosomesNum, int ElitistParentChromosomesNum, LD * GenesLeftLim, LD * GenesRightLim)
363 {
364 clock_t start = Encoding(ParentChromosomesNum, GenesNum, PullChromosomesNum, ElitistParentChromosomesNum, GenesLeftLim, GenesRightLim);
365 int iterationNum = Recombination(ParentChromosomesNum, GenesNum, PullChromosomesNum, ElitistParentChromosomesNum, GenesLeftLim, GenesRightLim);
366 clock_t finish = clock();
367 LD duration = (LD)(finish - start) / CLOCKS_PER_SEC;
368 OutputScreen(iterationNum, duration);
369 return x[0];
370 }
展开代码
4.编译（生成----生成解决方案）
编译之后，EDBFDLL.dll文件和EDBFDLL.lib文件在...\EDBFDLL\Debug目录下生成；EDBFDLL.h文件位于...\EDBFDLL\EDBFDLL目录下。
5.调用编译好的EDBFDLL.dll, EDBFDLL.lib和EDBFDLL.h文件
5.1 新建一个Win32控制台应用程序，并分别配置以上文件。
项目名称（右键）-----属性-------配置属性----- C/C++-------常规-------附加包含目录-------录入EDBFDLL.h文件所在的目录。
链接器-------常规-------附加库目录-------录入EDBFDLL.lib文件所在的目录。
链接器-------输入-------附加依赖项-------录入EDBFDLL.lib。
将EDBFDLL.dll拷贝至新项目的...\项目名\Debug目录下。
5.2 调用代码
1 // dlltest.cpp : 定义控制台应用程序的入口点。
2 //
3 #include "stdafx.h"
4 #include "EDBFDLL.h"
5 int main()
6 {
7 EDBFDLL * _EDBF = new EDBFDLL();
8 LD * GenesLeftLim = new LD[3];
9 LD * GenesRightLim = new LD[3];
10 for (int i = 0; i < 3; i++)
11 {
12 GenesLeftLim[i] = -30;
13 GenesRightLim[i] = 30;
14 }
15 EDBFDLL::B optimal = _EDBF->ED_BF(15, 3, 100, 5, GenesLeftLim, GenesRightLim);
16 _EDBF->DeleteSpace();
17 return 0;
18 }
展开代码