matpower解决linprog的错误补丁

function [x, f, eflag, output, lambda] = miqps_ot(H, c, A, l, u, xmin, xmax, x0, vtype, opt) %MIQPS_OT Mixed Integer Linear Program Solver based on INTLINPROG. % [X, F, EXITFLAG, OUTPUT, LAMBDA] = ... % MIQPS_OT(H, C, A, L, U, XMIN, XMAX, X0, VTYPE, OPT) % [X, F, EXITFLAG, OUTPUT, LAMBDA] = MIQPS_OT(PROBLEM) % A wrapper function providing a standardized interface for using % QUADPROG or LINPROG from the Optimization Toolbox to solve the % following QP (quadratic programming) problem: % % min 1/2 X'*H*X + C'*X % X % % subject to % % L <= A*X <= U (linear constraints) % XMIN <= X <= XMAX (variable bounds) % % Inputs (all optional except H, C, A and L): % H : matrix (possibly sparse) of quadratic cost coefficients % C : vector of linear cost coefficients % A, L, U : define the optional linear constraints. Default % values for the elements of L and U are -Inf and Inf, % respectively. % XMIN, XMAX : optional lower and upper bounds on the % X variables, defaults are -Inf and Inf, respectively. % X0 : optional starting value of optimization vector X % VTYPE : character string of length NX (number of elements in X), % or 1 (value applies to all variables in x), % allowed values are 'C' (continuous), 'B' (binary) or % 'I' (integer). % OPT : optional options structure with the following fields, % all of which are also optional (default values shown in % parentheses) % verbose (0) - controls level of progress output displayed % 0 = no progress output % 1 = some progress output % 2 = verbose progress output % skip_prices (0) - flag that specifies whether or not to % skip the price computation stage, in which the problem % is re-solved for only the continuous variables, with all % others being constrained to their solved values % price_stage_warn_tol (1e-7) - tolerance on the objective fcn % value and primal variable relative match required to avoid % mis-match warning message % intlinprog_opt - options struct for INTLINPROG, value in verbose % overrides these options % linprog_opt - options struct for LINPROG, value in verbose % overrides these options % PROBLEM : The inputs can alternatively be supplied in a single % PROBLEM struct with fields corresponding to the input arguments % described above: H, c, A, l, u, xmin, xmax, x0, vtype, opt % % Outputs: % X : solution vector % F : final objective function value % EXITFLAG : QUADPROG/LINPROG exit flag % (see QUADPROG and LINPROG documentation for details) % OUTPUT : QUADPROG/LINPROG output struct % (see QUADPROG and LINPROG documentation for details) % LAMBDA : struct containing the Langrange and Kuhn-Tucker % multipliers on the constraints, with fields: % mu_l - lower (left-hand) limit on linear constraints % mu_u - upper (right-hand) limit on linear constraints % lower - lower bound on optimization variables % upper - upper bound on optimization variables % % Note the calling syntax is almost identical to that of QUADPROG % from MathWorks' Optimization Toolbox. The main difference is that % the linear constraints are specified with A, L, U instead of % A, B, Aeq, Beq. % % Calling syntax options: % [x, f, exitflag, output, lambda] = ... % miqps_ot(H, c, A, l, u, xmin, xmax, x0, vtype, opt) % % x = miqps_ot(H, c, A, l, u) % x = miqps_ot(H, c, A, l, u, xmin, xmax) % x = miqps_ot(H, c, A, l, u, xmin, xmax, x0) % x = miqps_ot(H, c, A, l, u, xmin, xmax, x0, vtype) % x = miqps_ot(H, c, A, l, u, xmin, xmax, x0, vtype, opt) % x = miqps_ot(problem), where problem is a struct with fields: % H, c, A, l, u, xmin, xmax, x0, vtype, opt % all fields except 'c', 'A' and 'l' or 'u' are optional % x = miqps_ot(...) % [x, f] = miqps_ot(...) % [x, f, exitflag] = miqps_ot(...) % [x, f, exitflag, output] = miqps_ot(...) % [x, f, exitflag, output, lambda] = miqps_ot(...) % % % Example: (problem from from https://v8doc.sas.com/sashtml/iml/chap8/sect12.htm) % H = [ 1003.1 4.3 6.3 5.9; % 4.3 2.2 2.1 3.9; % 6.3 2.1 3.5 4.8; % 5.9 3.9 4.8 10 ]; % c = zeros(4,1); % A = [ 1 1 1 1; % 0.17 0.11 0.10 0.18 ]; % l = [1; 0.10]; % u = [1; Inf]; % xmin = zeros(4,1); % x0 = [1; 0; 0; 1]; % opt = struct('verbose', 2); % [x, f, s, out, lambda] = miqps_ot(H, c, A, l, u, xmin, [], x0, vtype, opt); % % See also MIQPS_MASTER, INTLINPROG, QUADPROG, LINPROG. % MP-Opt-Model % Copyright (c) 2010-2020, Power Systems Engineering Research Center (PSERC) % by Ray Zimmerman, PSERC Cornell % % This file is part of MP-Opt-Model. % Covered by the 3-clause BSD License (see LICENSE file for details). % See https://github.com/MATPOWER/mp-opt-model for more info. %% check for Optimization Toolbox % if ~have_feature('quadprog') % error('miqps_ot: requires the Optimization Toolbox'); % end %%----- input argument handling ----- %% gather inputs if nargin == 1 && isstruct(H) %% problem struct p = H; if isfield(p, 'opt'), opt = p.opt; else, opt = []; end if isfield(p, 'vtype'), vtype = p.vtype;else, vtype = []; end if isfield(p, 'x0'), x0 = p.x0; else, x0 = []; end if isfield(p, 'xmax'), xmax = p.xmax; else, xmax = []; end if isfield(p, 'xmin'), xmin = p.xmin; else, xmin = []; end if isfield(p, 'u'), u = p.u; else, u = []; end if isfield(p, 'l'), l = p.l; else, l = []; end if isfield(p, 'A'), A = p.A; else, A = []; end if isfield(p, 'c'), c = p.c; else, c = []; end if isfield(p, 'H'), H = p.H; else, H = []; end else %% individual args if nargin < 10 opt = []; if nargin < 9 vtype = []; if nargin < 8 x0 = []; if nargin < 7 xmax = []; if nargin < 6 xmin = []; end end end end end end %% define nx, set default values for missing optional inputs if isempty(H) || ~any(any(H)) if isempty(A) && isempty(xmin) && isempty(xmax) error('miqps_ot: LP problem must include constraints or variable bounds'); else if ~isempty(A) nx = size(A, 2); elseif ~isempty(xmin) nx = length(xmin); else % if ~isempty(xmax) nx = length(xmax); end end else nx = size(H, 1); end if isempty(c) c = zeros(nx, 1); end if isempty(A) || (~isempty(A) && (isempty(l) || all(l == -Inf)) && ... (isempty(u) || all(u == Inf))) A = sparse(0,nx); %% no limits => no linear constraints end nA = size(A, 1); %% number of original linear constraints if isempty(u) %% By default, linear inequalities are ... u = Inf(nA, 1); %% ... unbounded above and ... end if isempty(l) l = -Inf(nA, 1); %% ... unbounded below. end if isempty(xmin) %% By default, optimization variables are ... xmin = -Inf(nx, 1); %% ... unbounded below and ... end if isempty(xmax) xmax = Inf(nx, 1); %% ... unbounded above. end if isempty(x0) x0 = zeros(nx, 1); end if isempty(H)