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C語言實現基本PSO算法

介紹看此文：http://www.linuxidc.com/Linux/2012-11/73567.htm

粒子群算法的流程圖如上，看了好多版本，這個最靠譜，我的main函數完全按照這個來，好理解過程：

  1. int main(int argc, constchar *argv[])
  2. {
  3. int n=0;
  4. //printf("Random Initialization of the swarm:\n\n");
  5. RandInitofSwarm();
  6. //printf("Computation of the fitness of each particle:\n");
  7. ComputFitofSwarm();
  8. //printf("FirstComputPandGbest:\n");
  9. FirstComputPandGbest();
  10. while(n++!=N)
  11. {
  12. printf("The %dth time to calculate .\n",n );
  13. //printf("Updated of the swarm:\n\n");
  14. UpdateofVandX();
  15. //printf("Updated of the swarm's Fitness:\n");
  16. ComputFitofSwarm();
  17. //printf("Replaced of P and Gbest:\n\n");
  18. UpdatePandGbest();
  19. }
  20. getchar();
  21. return 0;
  22. }

各種printf用來調試自己的信息，可以去掉看看中間值～～～

先來pso.h
 
現在執行最簡單的功能，用粒子群搜索二維空間：y=x^2+y^+3的最大值～～～x,y的范圍屬於（-100,100）,那最大值就是20003,偽隨機粒子數20個，最大迭代次數為40次，最大搜索速度為2,慣性權重W設為1.4，學習因子c1=c2=2，看能不能找到最大值～～～

  1. #ifndef _PSO_H_
  2. #define _PSO_H_
  4. #define Dim 2
  5. #define PNum 20
  6. #define N 40
  8. typedefstruct PARTICLE{
  9. double X[Dim];
  10. double P[Dim];
  11. double V[Dim];
  12. double Fitness;
  13. }particle;
  15. typedefstruct SWARM{
  16. particle Particle[PNum];
  17. int GBestIndex;
  18. double GBest[Dim];
  19. double W;
  20. double C1;
  21. double C2;
  22. double Xup[Dim];
  23. double Xdown[Dim];
  24. double Vmax[Dim];
  25. }swarm;
  27. void RandInitofSwarm(void);
  28. void ComputFitofSwarm(void);
  29. void FirstComputPandGbest(void);
  30. void UpdateofVandX(void);
  31. void UpdatePandGbest(void);
  33. double InertWeight(void);
  34. int CriteriaofStop(void);
  36. #endif

pso.c

  1. #include "stdio.h"
  2. #include "stdlib.h"
  3. #include "time.h"
  4. #include "math.h"
  5. #include "pso.h"
  6. #include "stdio.h"
  8. swarm *s=(swarm *)malloc(sizeof(swarm));
  9. particle *p=(particle *)malloc(sizeof(particle));
  11. int main(int argc, constchar *argv[])
  12. {
  13. int n=0;
  14. //printf("Random Initialization of the swarm:\n\n");
  15. RandInitofSwarm();
  16. //printf("Computation of the fitness of each particle:\n");
  17. ComputFitofSwarm();
  18. //printf("FirstComputPandGbest:\n");
  19. FirstComputPandGbest();
  20. while(n++!=N)
  21. {
  22. printf("The %dth time to calculate .\n",n );
  23. //printf("Updated of the swarm:\n\n");
  24. UpdateofVandX();
  25. //printf("Updated of the swarm's Fitness:\n");
  26. ComputFitofSwarm();
  27. //printf("Replaced of P and Gbest:\n\n");
  28. UpdatePandGbest();
  29. }
  30. getchar();
  31. return 0;
  32. }
  34. //Random Initialization of the swarm
  35. void RandInitofSwarm(void)
  36. {
  37. int i,j;
  39. s->W=1.4;
  40. s->C1=2.0;
  41. s->C2=2.0;
  42. for(j=0;j<Dim;j++)
  43. {
  44. s->Xdown[j] = -100;
  45. s->Xup[j] = 100;
  46. s->Vmax[j] = 2;
  47. }
  49. srand((unsigned)time(NULL));
  50. for(i=0; i<PNum; i++)
  51. {
  52. //printf(" The %dth of X is: ",i);
  53. for(j=0; j<Dim; j++)
  54. {
  55. s->Particle[i].X[j] = rand()/(double)RAND_MAX*(s->Xup[j]-s->Xdown[j])+s->Xdown[j]; //-100~100
  56. s->Particle[i].V[j] = rand()/(double)RAND_MAX*s->Vmax[j]*2-s->Vmax[j]; //-2~2
  57. //printf(" %.2f \n ",s->Particle[i].X[j]);
  58. }
  59. }
  60. }
  62. //Computation of the fitness of each particle
  63. void ComputFitofSwarm(void)
  64. {
  65. int i;
  66. srand((unsigned)time(NULL));
  67. for(i=0; i<PNum; i++)
  68. {
  69. //printf(" The Fitness of %dth Particle: ",i);
  70. s->Particle[i].Fitness = s->Particle[i].X[0]*s->Particle[i].X[0]+s->Particle[i].X[1]*s->Particle[i].X[1]+3;
  71. //printf(" %.2f\n",s->Particle[i].Fitness);
  72. }
  73. }
  75. void FirstComputPandGbest(void)
  76. {
  77. int i,j;
  78. //P=X;
  79. for(i=0; i<PNum; i++)
  80. {
  81. for(j=0;j<Dim;j++)
  82. {
  83. s->Particle[i].P[j]=s->Particle[i].X[j];
  84. }
  85. }
  86. //Computation of GBest
  87. s->GBestIndex = 0;
  88. for(i=0; i<PNum; i++)
  89. if(s->Particle[i].Fitness>=s->Particle[s->GBestIndex].Fitness)
  90. s->GBestIndex = i;
  91. for(j=0;j<Dim;j++)
  92. {
  93. s->GBest[j]=s->Particle[s->GBestIndex].P[j];
  94. }
  95. printf("GBestIndex , GBest , Fitness of GBest:%d ,%.2f ,%.2f ,%.2f \n",
  96. s->GBestIndex ,s->GBest[0],s->GBest[1],
  97. s->Particle[s->GBestIndex].Fitness);
  98. }
  99. //update V and X
  100. void UpdateofVandX(void)
  101. {
  102. int i,j;
  103. srand((unsigned)time(NULL));
  104. for(i=0; i<PNum; i++)
  105. {
  106. //printf(" The %dth of X is: ",i);
  107. for(j=0; j<Dim; j++)
  108. s->Particle[i].V[j] = s->W*s->Particle[i].V[j]+
  109. rand()/(double)RAND_MAX*s->C1*(s->Particle[i].P[j] - s->Particle[i].X[j])+
  110. rand()/(double)RAND_MAX*s->C2*(s->GBest[j] - s->Particle[i].X[j]);
  111. for(j=0; j<Dim; j++)
  112. {
  113. if(s->Particle[i].V[j]>s->Vmax[j])
  114. s->Particle[i].V[j] = s->Vmax[j];
  115. if(s->Particle[i].V[j]<-s->Vmax[j])
  116. s->Particle[i].V[j] = -s->Vmax[j];
  117. }
  119. for(j=0; j<Dim; j++)
  120. {
  121. s->Particle[i].X[j] += s->Particle[i].V[j];
  122. if(s->Particle[i].X[j]>s->Xup[j])
  123. s->Particle[i].X[j]=s->Xup[j];
  124. if(s->Particle[i].X[j]<s->Xdown[j])
  125. s->Particle[i].X[j]=s->Xdown[j];
  126. }
  127. //printf(" %.2f %.2f \n",s->Particle[i].X[0],s->Particle[i].X[1]);
  128. }
  129. }
  131. staticdouble ComputAFitness(double X[])
  132. {
  133. return X[0]*X[0]+X[1]*X[1]+3;
  134. }
  135. void UpdatePandGbest(void)
  136. {
  137. int i,j;
  138. //update of P if the X is bigger than current P
  139. for (i = 0; i < PNum; i++)
  140. {
  141. //printf(" The %dth of P is: ",i);
  142. if (s->Particle[i].Fitness > ComputAFitness(s->Particle[i].P))
  143. {
  144. for(j=0;j<Dim;j++)
  145. {
  146. s->Particle[i].P[j] = s->Particle[i].X[j];
  147. }
  148. }
  149. //printf(" %.2f %.2f \n",s->Particle[i].P[0],s->Particle[i].P[1]);
  150. }
  151. for (i = 0; i < PNum; i++)
  152. {
  153. //printf("The %dth of P's Fitness is : %.2f \n",i,ComputAFitness(s->Particle[i].P));
  154. }
  155. //update of GBest
  156. for(i=0; i<PNum; i++)
  157. if(ComputAFitness(s->Particle[i].P) >= s->Particle[s->GBestIndex].Fitness)
  158. s->GBestIndex = i;
  159. for(j=0;j<Dim;j++)
  160. {
  161. s->GBest[j]=s->Particle[s->GBestIndex].P[j];
  162. }
  163. printf("GBestIndex , GBest , Fitness of GBest:%d ,%.2f ,%.2f ,%.2f \n",
  164. s->GBestIndex ,s->GBest[0],s->GBest[1],
  165. ComputAFitness(s->GBest));
  166. }
  168. double InertWeight(void)
  169. {
  170. return 1.0;
  171. }
  172. int CriteriaofStop()
  173. {
  174. int n=N;
  175. return (n--==0);
  176. }

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