Автоматизация управления техническими запасами.

Содержание


Введение
1. Постановка проектной задачи
2. Характеристика запасов на промышленных предприятиях
3. Задачи планирования запасов
4. Однопродуктовая динамическая модель управления запасами
5. Алгоритм оптимизации запасов в среде пакета MATLAB
6. Управление запасами в логистических сетях
7. Информатизация процессов управления запасами
8. Web-технологии в автоматизированных системах управления запасами
9. Web-браузер как средство доступа к БД
Заключение
Список источников
Приложение

Автоматизация управления техническими запасами.

% min f'*x such that A*x = b, x >= 0.
% The dual problem is
% max b'*y such that A'*y + s = f, s >= 0.
%
% See also QUADPROG.

% Copyright 1990-2008 The MathWorks, Inc.
% $Revision.2 $ $Date: 2008/06/20 08:05:10 $

% If just 'defaults' passed in, return the default options in X

% Default MaxIter is set to [] because its value depends on the algorithm.
defaultopt = struct('Display','final',...
'TolFun',[],'Diagnostics','off',...
'LargeScale','on','MaxIter',[], ...
'Simplex','off');

if nargin==1 && nargout <= 1 && isequal(f,'defaults')
x = defaultopt;
return
end

% Handle missing arguments
if nargin < 9, options = [];
if nargin < 8, x0 = [];
if nargin < 7, ub = [];
if nargin < 6, lb =[];
if nargin < 5, Beq = [];
if nargin < 4, Aeq = [];
end, end, end, end, end, end

% Detect problem structure input
problemInput = false;
if nargin == 1
if isa(f,'struct')
problemInput = true;
[f,A,B,Aeq,Beq,lb,ub,x0,options] = separateOptimStruct(f);
else % Single input and non-structure.
error('optim:linprog:InputArg','The input to LINPROG should be either a structure with valid fields or consist of at least three arguments.');
end
end

if nargin < 3 && ~problemInput
error('optim:linprog:NotEnoughInputs','LINPROG requires at least three input arguments.')
end

% Check for non-double inputs
% SUPERIORFLOAT errors when superior input is neither single nor double;
% We use try-catch to override SUPERIORFLOAT's error message when input
% data type is integer.
try
dataType = superiorfloat(f,A,B,Aeq,Beq,lb,ub,x0);
catch ME
if strcmp(ME.identifier,'MATLAB:datatypes:superiorfloat')
dataType = 'notDouble';
end
end

if ~strcmp(dataType,'double')
error('optim:linprog:NonDoubleInput', ...
'LINPROG only accepts inputs of data type double.')
end

if nargout > 4
computeLambda = 1;
else
computeLambda = 0;
end

% Options setup
if isfield(options,'Simplex')
useSimplex = isequal(optimget(options,'Simplex',defaultopt,'fast'), 'on');
else
useSimplex = isequal(defaultopt.Simplex, 'on');
end

largescale = isequal(optimget(options,'LargeScale',defaultopt,'fast'),'on');
diagnostics = isequal(optimget(options,'Diagnostics',defaultopt,'fast'),'on');
switch optimget(options,'Display',defaultopt,'fast')
case {'off','none'}
verbosity = 0;
case 'iter'
verbosity = 2;
case 'final'
verbosity = 1;
otherwise
verbosity = 1;
end

% Set the constraints up: defaults and check size
[nineqcstr,nvarsineq]=size(A);
[neqcstr, nvarseq]=size(Aeq);
nvars = max([length(f),nvarsineq,nvarseq]); % In case A is empty
ncstr = nineqcstr + neqcstr;

if isempty(f), f=zeros(nvars,1); end
if isempty(A), A=zeros(0,nvars); end
if isempty(B), B=zeros(0,1); end
if isempty(Aeq), Aeq=zeros(0,nvars); end
if isempty(Beq), Beq=zeros(0,1); end

% Set to column vectors
f = f(:);
B = B(:);
Beq = Beq(:);

if ~isequal(length(B),nineqcstr)
error('optim:linprog:SizeMismatchRowsOfA', ...
'The number of rows in A must be the same as the length of b.');
elseif ~isequal(length(Beq),neqcstr)
error('optim:linprog:SizeMismatchRowsOfAeq', ...
'The number of rows in Aeq must be the same as the length of beq.');
elseif ~isequal(length(f),nvarsineq) && ~isempty(A)
error('optim:linprog:SizeMismatchColsOfA', ...
'The number of columns in A must be the same as the length of f.');
elseif ~isequal(length(f),nvarseq) && ~isempty(Aeq)
error('optim:linprog:SizeMismatchColsOfAeq', ...
'The number of columns in Aeq must be the same as the length of f.');
end

[x0,lb,ub,msg] = checkbounds(x0,lb,ub,nvars);
if ~isempty(msg)
exitflag = -2;
x=x0; fval = []; lambda = [];
output.iterations = 0;
output.algorithm = ''; % not known at this stage
output.cgiterations = [];
output.message = msg;
if verbosity > 0
disp(msg)
end
return
end

caller = 'linprog';
ncstr = nineqcstr + neqcstr;

if largescale
OUTPUT.algorithm = 'large-scale: interior point';
elseif useSimplex
OUTPUT.algorithm = 'medium-scale: simplex';
else
OUTPUT.algorithm = 'medium-scale: active-set';
end

if diagnostics
% Do diagnostics on information so far
gradflag = []; hessflag = []; line_search=[];
constflag = 0; gradconstflag = 0; non_eq=0;non_ineq=0;
lin_eq=size(Aeq,1); lin_ineq=size(A,1); XOUT=ones(nvars,1);
funfcn{1} = [];ff=[]; GRAD=[];HESS=[];
confcn{1}=[];c=[];ceq=[];cGRAD=[];ceqGRAD=[];
msg = diagnose('linprog',OUTPUT,gradflag,hessflag,constflag,gradconstflag,...
line_search,options,defaultopt,XOUT,non_eq,...
non_ineq,lin_eq,lin_ineq,lb,ub,funfcn,confcn,ff,GRAD,HESS,c,ceq,cGRAD,ceqGRAD);
end

if (largescale)
if (useSimplex)
warning('optim:linprog:IgnoreSimplexOn', ...
['Simplex method does not currently solve large-scale problems;\n' ...
'calling large-scale interior point method. (To run simplex, set\n' ...
'OPTIONS.LargeScale to ''off''.)'])
end
if ~isempty(x0) && verbosity > 0
warning('optim:linprog:IgnoreStartPoint', ...
['Large scale (interior point) method uses a built-in starting point;\n' ...
'ignoring user-supplied X0.'])
end
% Set the default values of TolFun and MaxIter for this algorithm
defaultopt.TolFun = 1e-8;
defaultopt.MaxIter = 85;
[x,fval,lambda,exitflag,output] = lipsol(f,A,B,Aeq,Beq,lb,ub,options,defaultopt,computeLambda);
elseif (useSimplex)
if ~isempty(x0) && verbosity > 0
warning('optim:linprog:IgnoreStartPoint', ...