fmincon.m

matpower软件下

         ['Medium-scale method is a Quasi-Newton method and does not use\n' ...
         'analytic Hessian. Hessian flag in options will be ignored.'])
   elseif  isequal(funfcn{1},'fun_then_grad_then_hess')
      funfcn{1}='fun_then_grad';
      warning('optim:fmincon:HessianIgnored', ...
         ['Medium-scale method is a Quasi-Newton method and does not use\n' ...
         'analytic Hessian. Hessian flag in options will be ignored.'])
   end    
   hessflag = 0;
   OUTPUT.algorithm = medium;
elseif line_search
   OUTPUT.algorithm = medium;
   if issparse(Aeq) || issparse(A)
      warning('optim:fmincon:ConvertingToFull', ...
              'Cannot use sparse matrices with medium-scale method: converting to full.')
   end
   if line_search && hessflag % conflicting options
      hessflag = 0;
      warning('optim:fmincon:HessianIgnored', ...
         ['Medium-scale method is a Quasi-Newton method and does not use analytic Hessian.\n' ...
         'Hessian flag in options will be ignored (user-supplied Hessian will not be used).']);      
      if isequal(funfcn{1},'fungradhess')
         funfcn{1}='fungrad';
      elseif  isequal(funfcn{1},'fun_then_grad_then_hess')
         funfcn{1}='fun_then_grad';
      end    
   end
   % else call nlconst
else
   error('optim:fmincon:InvalidOptions', ...
      'Unrecognized combination of OPTIONS flags and calling sequence.')
end


lenvlb=length(l);
lenvub=length(u);

if isequal(OUTPUT.algorithm,medium)
   %
   % Ensure starting point lies within bounds
   %
   i=1:lenvlb;
   lindex = XOUT(i)<l(i);
   if any(lindex),
      XOUT(lindex)=l(lindex)+1e-4; 
   end
   i=1:lenvub;
   uindex = XOUT(i)>u(i);
   if any(uindex)
      XOUT(uindex)=u(uindex);
   end
   X(:) = XOUT;
else
   %
   % If initial x not within bounds, set it a to a "box-centered" point
   %
   arg = (u >= 1e10); arg2 = (l <= -1e10);
   u(arg) = inf*ones(length(arg(arg>0)),1);
   l(arg2) = -inf*ones(length(arg2(arg2>0)),1);
   if min(min(u-XOUT),min(XOUT-l)) < 0, 
      XOUT = startx(u,l);
      X(:) = XOUT;
   end
end

% Evaluate function
GRAD=zeros(numberOfVariables,1);
HESS = [];

switch funfcn{1}
case 'fun'
   try
      f = feval(funfcn{3},X,varargin{:});
   catch
     error('optim:fmincon:ObjectiveError', ...
            ['FMINCON cannot continue because user supplied objective function' ...
             ' failed with the following error:\n%s'], lasterr)
   end
case 'fungrad'
   try
      [f,GRAD(:)] = feval(funfcn{3},X,varargin{:});
   catch 
      error('optim:fmincon:ObjectiveError', ...
           ['FMINCON cannot continue because user supplied objective function' ...
            ' failed with the following error:\n%s'], lasterr)
   end
case 'fungradhess'
   try
      [f,GRAD(:),HESS] = feval(funfcn{3},X,varargin{:});
   catch
     error('optim:fmincon:ObjectiveError', ...
            ['FMINCON cannot continue because user supplied objective function' ...
             ' failed with the following error:\n%s'], lasterr)
   end
case 'fun_then_grad'
   try
      f = feval(funfcn{3},X,varargin{:});
   catch
     error('optim:fmincon:ObjectiveError', ...
            ['FMINCON cannot continue because user supplied objective function' ...
             ' failed with the following error:\n%s'], lasterr)
   end
   try
      GRAD(:) = feval(funfcn{4},X,varargin{:});
   catch
      error('optim:fmincon:GradError', ...
            ['FMINCON cannot continue because user supplied objective gradient function' ...
             ' failed with the following error:\n%s'], lasterr)
   end
case 'fun_then_grad_then_hess'
   try
      f = feval(funfcn{3},X,varargin{:});
   catch
      error('optim:fmincon:ObjectiveError', ...
            ['FMINCON cannot continue because user supplied objective function' ...
             ' failed with the following error:\n%s'], lasterr)
   end
   try
      GRAD(:) = feval(funfcn{4},X,varargin{:});
   catch
      error('optim:fmincon:GradientError', ...
            ['FMINCON cannot continue because user supplied objective gradient function' ...
             ' failed with the following error:\n%s'], lasterr)     
   end
   try
      HESS = feval(funfcn{5},X,varargin{:});
   catch 
      error('optim:fmincon:HessianError', ...
            ['FMINCON cannot continue because user supplied objective Hessian function' ...
             ' failed with the following error:\n%s'], lasterr)     
   end
otherwise
   error('optim:fmincon:UndefinedCallType','Undefined calltype in FMINCON.');
end

% Evaluate constraints
switch confcn{1}
case 'fun'
   try 
      [ctmp,ceqtmp] = feval(confcn{3},X,varargin{:});
      c = ctmp(:); ceq = ceqtmp(:);
      cGRAD = zeros(numberOfVariables,length(c));
      ceqGRAD = zeros(numberOfVariables,length(ceq));
   catch
      if findstr(xlate('Too many output arguments'),lasterr)
          if isa(confcn{3},'inline')
              error('optim:fmincon:InvalidInlineNonlcon', ...
                ['The inline function %s representing the constraints\n' ...
                 ' must return two outputs: the nonlinear inequality constraints and\n' ...
                 ' the nonlinear equality constraints.  At this time, inline objects may\n' ...
                 ' only return one output argument: use an M-file function instead.'], ...
                    formula(confcn{3}))            
          elseif isa(confcn{3},'function_handle')
              error('optim:fmincon:InvalidHandleNonlcon', ...
                   ['The constraint function %s must return two outputs:\n' ...
                    ' the nonlinear inequality constraints and\n' ...
                    ' the nonlinear equality constraints.'],func2str(confcn{3}))            
          else
              error('optim:fmincon:InvalidFunctionNonlcon', ...
                   ['The constraint function %s must return two outputs:\n' ...
                    ' the nonlinear inequality constraints and\n' ...
                    ' the nonlinear equality constraints.'],confcn{3})
          end
      else
        error('optim:fmincon:NonlconError', ... 
            ['FMINCON cannot continue because user supplied nonlinear constraint function\n' ...
            ' failed with the following error:\n%s'],lasterr)        
      end
   end
   
case 'fungrad'
   try
      [ctmp,ceqtmp,cGRAD,ceqGRAD] = feval(confcn{3},X,varargin{:});
      c = ctmp(:); ceq = ceqtmp(:);
   catch
      error('optim:fmincon:NonlconError', ... 
           ['FMINCON cannot continue because user supplied nonlinear constraint function\n' ...
            ' failed with the following error:\n%s'],lasterr)  
   end
case 'fun_then_grad'
   try
      [ctmp,ceqtmp] = feval(confcn{3},X,varargin{:});
      c = ctmp(:); ceq = ceqtmp(:);
      [cGRAD,ceqGRAD] = feval(confcn{4},X,varargin{:});
   catch
      error('optim:fmincon:NonlconFunOrGradError', ... 
           ['FMINCON cannot continue because user supplied nonlinear constraint function\n' ...
            'or nonlinear constraint gradient function failed with the following error:\n%s'],lasterr) 
   end
case ''
   c=[]; ceq =[];
   cGRAD = zeros(numberOfVariables,length(c));
   ceqGRAD = zeros(numberOfVariables,length(ceq));
otherwise
   error('optim:fmincon:UndefinedCalltype','Undefined calltype in FMINCON.');
end

non_eq = length(ceq);
non_ineq = length(c);
[lin_eq,Aeqcol] = size(Aeq);
[lin_ineq,Acol] = size(A);
[cgrow, cgcol]= size(cGRAD);
[ceqgrow, ceqgcol]= size(ceqGRAD);

eq = non_eq + lin_eq;
ineq = non_ineq + lin_ineq;

if ~isempty(Aeq) && Aeqcol ~= numberOfVariables
   error('optim:fmincon:WrongNumberOfColumnsInAeq','Aeq has the wrong number of columns.')
end
if ~isempty(A) && Acol ~= numberOfVariables
   error('optim:fmincon:WrongNumberOfColumnsInA','A has the wrong number of columns.')
end
if  cgrow~=numberOfVariables && cgcol~=non_ineq
   error('optim:fmincon:WrongSizeGradNonlinIneq', ...
         'Gradient of the nonlinear inequality constraints is the wrong size.')
end
if ceqgrow~=numberOfVariables && ceqgcol~=non_eq
   error('optim:fmincon:WrongSizeGradNonlinEq', ...
         'Gradient of the nonlinear equality constraints is the wrong size.')
end

if diagnostics > 0
   % Do diagnostics on information so far
   msg = diagnose('fmincon',OUTPUT,gradflag,hessflag,constflag,gradconstflag,...
      line_search,options,defaultopt,XOUT,non_eq,...
      non_ineq,lin_eq,lin_ineq,l,u,funfcn,confcn,f,GRAD,HESS,c,ceq,cGRAD,ceqGRAD);
end


% call algorithm
if isequal(OUTPUT.algorithm,medium)
   [X,FVAL,lambda,EXITFLAG,OUTPUT,GRAD,HESSIAN]=...
      nlconst(funfcn,X,l,u,full(A),B,full(Aeq),Beq,confcn,options,defaultopt, ...
      verbosity,gradflag,gradconstflag,hessflag,meritFunctionType,...
      f,GRAD,HESS,c,ceq,cGRAD,ceqGRAD,varargin{:});
   LAMBDA=lambda;
   
   
else
   if (isequal(funfcn{1}, 'fun_then_grad_then_hess') || isequal(funfcn{1}, 'fungradhess'))
      Hstr=[];
   elseif (isequal(funfcn{1}, 'fun_then_grad') || isequal(funfcn{1}, 'fungrad'))
      n = length(XOUT); 
      Hstr = optimget(options,'HessPattern',defaultopt,'fast');
      if ischar(Hstr) 
         if isequal(lower(Hstr),'sparse(ones(numberofvariables))')
            Hstr = sparse(ones(n));
         else
            error('optim:fmincon:InvalidHessPattern', ...
                  'Option ''HessPattern'' must be a matrix if not the default.')
         end
      end
   end
   
   if isempty(Aeq)
      [X,FVAL,LAMBDA,EXITFLAG,OUTPUT,GRAD,HESSIAN] = ...
         sfminbx(funfcn,X,l,u,verbosity,options,defaultopt,computeLambda,f,GRAD,HESS,Hstr,varargin{:});
   else
      [X,FVAL,LAMBDA,EXITFLAG,OUTPUT,GRAD,HESSIAN] = ...
         sfminle(funfcn,X,sparse(Aeq),Beq,verbosity,options,defaultopt,computeLambda,f,GRAD,HESS,Hstr,varargin{:});
   end
end