diff options
Diffstat (limited to 'build/Scilab')
| -rw-r--r-- | build/Scilab/intfmincon.sci | 51 |
1 files changed, 23 insertions, 28 deletions
diff --git a/build/Scilab/intfmincon.sci b/build/Scilab/intfmincon.sci index 9cf9116..0d6cf6d 100644 --- a/build/Scilab/intfmincon.sci +++ b/build/Scilab/intfmincon.sci @@ -207,14 +207,14 @@ function [xopt,fopt,exitflag,gradient,hessian] = intfmincon (varargin) //To check for correct size of A(3rd paramter) if(size(A,2)~=nbVar & size(A,2)~=0) then - errmsg = msprintf(gettext("%s: Expected Matrix of size (No of linear inequality constraints X No of Variables) or an Empty Matrix for Linear Inequality Constraint coefficient Matrix A"), solver_name); + errmsg = msprintf(gettext("%s: Expected Matrix of size (No of linear inequality constraints X No of Variables) or an Empty Matrix for Linear Inequality Constraint coefficient Matrix A"), intfmincon); error(errmsg); end nbConInEq=size(A,"r"); //To check for the correct size of Aeq (5th paramter) if(size(Aeq,2)~=nbVar & size(Aeq,2)~=0) then - errmsg = msprintf(gettext("%s: Expected Matrix of size (No of linear equality constraints X No of Variables) or an Empty Matrix for Linear Equality Constraint coefficient Matrix Aeq"), solver_name); + errmsg = msprintf(gettext("%s: Expected Matrix of size (No of linear equality constraints X No of Variables) or an Empty Matrix for Linear Equality Constraint coefficient Matrix Aeq"), intfmincon); error(errmsg); end nbConEq=size(Aeq,"r"); @@ -340,18 +340,18 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al if (type(nlc) == 13 | type(nlc) == 11) then if(execstr('[sample_c,sample_ceq] = nlc(x0)','errcatch')==21) then - errmsg = msprintf(gettext("%s: Non-Linear Constraint function and x0 did not match"), solver_name); + errmsg = msprintf(gettext("%s: Non-Linear Constraint function and x0 did not match"), intfmincon); error(errmsg); end numNlic = size(sample_c,"*"); numNlec = size(sample_ceq,"*"); - numNlc = no_nlic + no_nlec; + numNlc = numNlic + numNlec; end /////////////// Creating conLb and conUb //////////////////////// - conLb = [repmat(-%inf,nbConInEq,1);beq;repmat(-%inf,numNlic,1);repmat(0,numNlic,1);] - conUb = [b;beq;repmat(0,numNlic,1);repmat(0,numNlic,1);] + conLb = [repmat(-%inf,numNlic,1);repmat(0,numNlec,1);repmat(-%inf,nbConInEq,1);beq;] + conUb = [repmat(0,numNlic,1);repmat(0,numNlec,1);b;beq;] //Converting the User defined Objective function into Required form (Error Detectable) function [y,check] = _f(x) @@ -386,17 +386,13 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al endfunction function [y,check] = _addnlc(x) - x= x(:); - c=[] - ceq = []; + x= x(:) try - if(type(nlc) == 13 & numNlc~=0) then - { - [c,ceq] = nlc(x); - } + if((type(nlc) == 13 | type(nlc) == 11) & numNlc~=0) then + [c,ceq]=nlc(x) end ylin = [A*x;Aeq*x]; - y = [ylin;c(:);ceq(:)]; + y = [c(:);ceq(:);ylin(:);]; [y,check] = checkIsreal(y) catch y=0; @@ -404,11 +400,11 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al end endfunction - //Defining an inbuilt Objective gradient function + //Defining an inbuilt jacobian of constraints function function [dy,check] = _gradnlc(x) if (options(16) =="on") then try - [y,dy]=_addnlc(x) + [y,dy]=nlc(x) [dy,check] = checkIsreal(dy) catch dy = 0; @@ -427,6 +423,7 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al //Defining a function to calculate Hessian if the respective user entry is OFF function [hessy,check]=_gradhess(x,obj_factor,lambda) + x=x(:); if (type(options(14)) == "function") then try [obj,dy,hessy] = fun(x,obj_factor,lambda) @@ -437,17 +434,15 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al end else try - [dy,hessfy]=numderivative(_f,x,%eps^(1/3),1,"blockmat"); - hessny = [] - if(type(nlc) == 13 & numNlc~=0) then - { - [dy,hessny] = numderivative(_addnlc,x,%eps^(1/3),1,"blockmat"); - } + [dy,hessfy]=numderivative(_f,x) + hessfy = matrix(hessfy,nbVar,nbVar) + if((type(nlc) == 13 | type(nlc) == 11) & numNlc~=0) then + [dy,hessny]=numderivative(nlc,x) end hessianc = [] - for i = 1:numNlc - hessianc = hessianc + lambda(i)*hessny((i-1)*nbVar+1:nbVar*i,:) - end + for i = 1:numNlc + hessianc = hessianc + lambda(i)*matrix(hessny(i,:),nbVar,nbVar) + end hessy = obj_factor*hessfy + hessianc; [hessy,check] = checkIsreal(hessy) catch @@ -457,7 +452,7 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al end endfunction - intconsize = size(intcon,"*"); + intconsize = size(intcon,"*") [xopt,fopt,exitflag] = inter_fmincon(_f,_gradf,_addnlc,_gradnlc,_gradhess,x0,lb,ub,conLb,conUb,intcon,options,nbConInEq+nbConEq); @@ -466,7 +461,7 @@ options = list('integertolerance',1d-06,'maxnodes',2147483647,'cputime',1d10,'al gradient = []; hessian = []; else - [ gradient, hessian] = numderivative(_f, xopt, [], [], "blockmat"); + [ gradient, hessian] = numderivative(_f, xopt) end //To print output message @@ -495,7 +490,7 @@ function [y, check] = checkIsreal(x) y = 0 check=1; else - y = x; + y = x; check=0; end endfunction |