rc>0 means find a soultion |
---|
4 |
Hello,
I have a function I neet to optimize using PROC GA and it is simple -- 0.1*x*y. But then I have constraint which is not that simple x**2 + y**2 <= (5+2.2*cos(10*atan(x/y)))**2. How can I solve this in SAS? Sorry, I am very new with SAS. My code so far looks like:
proc ga seed = 12 maxiter = 30; function funkc(selected[*]); array x[2] /nosym; call ReadMember(selected,1,x); x1 = x[1]; x2 = x[2]; F= 0.1*x1*x2; return(F); endsub; call SetEncoding('R2'); array LowerBound[2] /nosym (-10 -6); array UpperBound[2] /nosym (10 6); call SetBounds(LowerBound, UpperBound); call SetObjFunc('funkc',0); call SetCrossProb(0.65); call SetCross('Heuristic'); call SetMutProb(0.15); array del[2] /nosym (0.2 0.2); call SetMut('Delta','nchange', 1, 'delta',del); call SetSel('tournament','size', 2); call SetElite(2); call Initialize('DEFAULT',150); run; quit;
I really suggest you to use Nonlinear Optimization Function, since GA can not guarantee you to get the optimal solution.
And better post it at IML forum.
If you want stick with PROC GA ,then post it at OR forum, since PROC GA is under SAS/OR.
proc iml;
start F_UC2D(x);
f = 0.1*x[1]*x[2];;
return(f);
finish F_UC2D;
start C_UC2D(x);
c = (5+2.2*cos(10*atan(x[1]/x[2])))**2 - x[1]**2 - x[2]**2 ;
return(c);
finish C_UC2D;
x = j(1,2,0.5);
optn= j(1,10,.);optn[1]=0; optn[2]= 1; optn[10]= 1;
CALL NLPNMS(rc,xres,"F_UC2D",x,optn) nlc="C_UC2D";
print rc[l='rc>0 means find a soultion'],xres[l='solution for x'];
quit;
ABSXCONV convergence criterion satisfied. |
rc>0 means find a soultion |
---|
4 |
solution for x | |
---|---|
-4.283178 | 5.7739759 |
I really suggest you to use Nonlinear Optimization Function, since GA can not guarantee you to get the optimal solution.
And better post it at IML forum.
If you want stick with PROC GA ,then post it at OR forum, since PROC GA is under SAS/OR.
proc iml;
start F_UC2D(x);
f = 0.1*x[1]*x[2];;
return(f);
finish F_UC2D;
start C_UC2D(x);
c = (5+2.2*cos(10*atan(x[1]/x[2])))**2 - x[1]**2 - x[2]**2 ;
return(c);
finish C_UC2D;
x = j(1,2,0.5);
optn= j(1,10,.);optn[1]=0; optn[2]= 1; optn[10]= 1;
CALL NLPNMS(rc,xres,"F_UC2D",x,optn) nlc="C_UC2D";
print rc[l='rc>0 means find a soultion'],xres[l='solution for x'];
quit;
ABSXCONV convergence criterion satisfied. |
rc>0 means find a soultion |
---|
4 |
solution for x | |
---|---|
-4.283178 | 5.7739759 |
I minimize object function,
If you want maximize it , use
optn[1]=1;
Registration is open! SAS is returning to Vegas for an AI and analytics experience like no other! Whether you're an executive, manager, end user or SAS partner, SAS Innovate is designed for everyone on your team. Register for just $495 by 12/31/2023.
If you are interested in speaking, there is still time to submit a session idea. More details are posted on the website.
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.