summaryrefslogtreecommitdiff
path: root/macros/qpipopt.sci
blob: 6a53693624f1f326010c1c811a374fbf6b925ad5 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
// Copyright (C) 2015 - IIT Bombay - FOSSEE
//
// Author: Harpreet Singh
// Organization: FOSSEE, IIT Bombay
// Email: harpreet.mertia@gmail.com
// This file must be used under the terms of the CeCILL.
// This source file is licensed as described in the file COPYING, which
// you should have received as part of this distribution.  The terms
// are also available at
// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt


function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin)
  // Solves a linear quadratic problem.
  //
  //   Calling Sequence
  //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
  //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0)
  //   xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param)
  //   [xopt,fopt,exitflag,output,lamda] = qpipopt( ... )
  //   
  //   Parameters
  //   nbVar : a double, number of variables
  //   nbCon : a double, number of constraints
  //   Q : a symmetric matrix of double, represents coefficients of quadratic in the quadratic problem.
  //   p : a vector of double, represents coefficients of linear in the quadratic problem
  //   LB : a vector of double, contains lower bounds of the variables.
  //   UB : a vector of double, contains upper bounds of the variables.
  //   conMatrix : a matrix of double, contains  matrix representing the constraint matrix 
  //   conLB : a vector of double, contains lower bounds of the constraints. 
  //   conUB : a vector of double, contains upper bounds of the constraints. 
  //   x0 : a vector of double, contains initial guess of variables.
  //   param : a list containing the the parameters to be set.
  //   xopt : a vector of double, the computed solution of the optimization problem.
  //   fopt : a double, the function value at x.
  //   exitflag : Integer identifying the reason the algorithm terminated.
  //   output : Structure containing information about the optimization. Right now it contains number of iteration.
  //   lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.
  //   
  //   Description
  //   Search the minimum of a constrained linear quadratic optimization problem specified by :
  //   find the minimum of f(x) such that 
  //
  //   <latex>
  //    \begin{eqnarray}
  //    &\mbox{min}_{x}
  //    & 1/2*x'*Q*x + p'*x  \\
  //    & \text{subject to} & conLB \leq C(x) \leq conUB \\
  //    & & lb \leq x \leq ub \\
  //    \end{eqnarray}
  //   </latex>
  //   
  //   We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++.
  //
  // Examples
  //      //Find x in R^6 such that:
  //      conMatrix= [1,-1,1,0,3,1;
  //                 -1,0,-3,-4,5,6;
  //                  2,5,3,0,1,0
  //                  0,1,0,1,2,-1;
  //                 -1,0,2,1,1,0];
  //      conLB=[1;2;3;-%inf;-%inf];
  //      conUB = [1;2;3;-1;2.5];
  //      lb=[-1000;-10000; 0; -1000; -1000; -1000];
  //      ub=[10000; 100; 1.5; 100; 100; 1000];
  //      //and minimize 0.5*x'*Q*x + p'*x with
  //      p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6);
  //      nbVar = 6;
  //      nbCon = 5;
  //      x0 = repmat(0,nbVar,1);
  //	  param = list("MaxIter", 300, "CpuTime", 100);
  //      [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)
  // // Press ENTER to continue
  //    
  // Examples 
  //    //Find the value of x that minimize following function
  //    // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
  //    // Subject to:
  //    // x1 + x2 ≤ 2
  //    // –x1 + 2x2 ≤ 2
  //    // 2x1 + x2 ≤ 3
  //    // 0 ≤ x1, 0 ≤ x2.
  //	Q = [1 -1; -1 2]; 
  //	p = [-2; -6];
  //    conMatrix = [1 1; -1 2; 2 1];
  //	conUB = [2; 2; 3];
  //	conLB = [-%inf; -%inf; -%inf];
  //	lb = [0; 0];
  //	ub = [%inf; %inf];
  //	nbVar = 2;
  //	nbCon = 3;
  //	[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
  // Authors
  // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
    
    
//To check the number of input and output argument
   [lhs , rhs] = argn();
	
//To check the number of argument given by user
   if ( rhs < 9 | rhs > 11 ) then
    errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "qpipopt", rhs);
    error(errmsg)
   end
   
   
   nbVar = varargin(1);
   nbCon = varargin(2);
   Q = varargin(3);
   p = varargin(4);
   LB = varargin(5);
   UB = varargin(6);
   conMatrix = varargin(7);
   conLB = varargin(8);
   conUB = varargin(9);

    if (size(LB,2)==0) then
        LB = repmat(-%inf,nbVar,1);
    end
    
    if (size(UB,2)==0) then
        UB = repmat(%inf,nbVar,1);
    end

    if (size(p,2)==0) then
        p = repmat(0,nbVar,1);
    end
    
    
   if ( rhs<10 | size(varargin(10)) ==0 ) then
      x0 = repmat(0,nbVar,1);
   else
      x0 = varargin(10);
  end
   
   if ( rhs<11 | size(varargin(11)) ==0 ) then
      param = list(); 
   else
      param =varargin(11);
   end
   
   if (type(param) ~= 15) then
      errmsg = msprintf(gettext("%s: param should be a list "), "qpipopt");
      error(errmsg);
   end
   
   if (modulo(size(param),2)) then
	errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt");
	error(errmsg);
   end


   options = list(..
      "MaxIter"     , [3000], ...
      "CpuTime"   , [600] ...
      );
      

   for i = 1:(size(param))/2
       	select param(2*i-1)
    	case "MaxIter" then
          		options(2*i) = param(2*i);
       	case "CpuTime" then
          		options(2*i) = param(2*i);
    	else
    	      errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1));
    	      error(errmsg)
    	end
   end

// Check if the user gives row vector 
// and Changing it to a column matrix

   if (size(p,2)== [nbVar]) then
   	p=p';
   end

   if (size(LB,2)== [nbVar]) then
	LB = LB';
   end

   if (size(UB,2)== [nbVar]) then
      UB = UB';
   end

   if (size(conUB,2)== [nbCon]) then
      conUB = conUB';
   end

   if (size(conLB,2)== [nbCon]) then
      conLB = conLB';
   end

   if (size(x0,2)== [nbVar]) then
	x0=x0';
   end

   //IPOpt wants it in row matrix form
   p = p';
   LB = LB';
   UB = UB';
   conLB = conLB';
   conUB = conUB';
   x0 = x0';
   
   //Checking the Q matrix which needs to be a symmetric matrix
   if ( ~isequal(Q,Q') ) then
      errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt");
      error(errmsg);
   end

   //Check the size of Q which should equal to the number of variable
   if ( size(Q) ~= [nbVar nbVar]) then
      errmsg = msprintf(gettext("%s: The Size of Q is not equal to the number of variables"), "qpipopt");
      error(errmsg);
   end
   
   //Check the size of p which should equal to the number of variable
   if ( size(p,2) ~= [nbVar]) then
      errmsg = msprintf(gettext("%s: The Size of p is not equal to the number of variables"), "qpipopt");
      error(errmsg);
   end
   
   if (nbCon) then
          //Check the size of constraint which should equal to the number of variables
       if ( size(conMatrix,2) ~= nbVar) then
          errmsg = msprintf(gettext("%s: The size of constraints is not equal to the number of variables"), "qpipopt");
          error(errmsg);
       end
   end

   //Check the number of constraint
   if ( size(conMatrix,1) ~= nbCon) then
      errmsg = msprintf(gettext("%s: The size of constraint matrix is not equal to the number of constraint given i.e. %d"), "qpipopt", nbCon);
      error(errmsg);
   end

   //Check the size of Lower Bound which should equal to the number of variables
   if ( size(LB,2) ~= nbVar) then
      errmsg = msprintf(gettext("%s: The size of Lower Bound is not equal to the number of variables"), "qpipopt");
      error(errmsg);
   end

   //Check the size of Upper Bound which should equal to the number of variables
   if ( size(UB,2) ~= nbVar) then
      errmsg = msprintf(gettext("%s: The size of Upper Bound is not equal to the number of variables"), "qpipopt");
      error(errmsg);
   end

   //Check the size of constraints of Lower Bound which should equal to the number of constraints
   if ( size(conLB,2) ~= nbCon) then
      errmsg = msprintf(gettext("%s: The size of Lower Bound of constraints is not equal to the number of constraints"), "qpipopt");
      error(errmsg);
   end

   //Check the size of constraints of Upper Bound which should equal to the number of constraints
   if ( size(conUB,2) ~= nbCon) then
      errmsg = msprintf(gettext("%s: The size of Upper Bound of constraints is not equal to the number of constraints"), "qpipopt");
      error(errmsg);
   end
    
   //Check the size of initial of variables which should equal to the number of variables
   if ( size(x0,2) ~= nbVar | size(x0,"*")>nbVar) then
      warnmsg = msprintf(gettext("%s: Ignoring initial guess of variables as it is not equal to the number of variables"), "qpipopt");
      warning(warnmsg);
   end
   
   //Check if the user gives a matrix instead of a vector
   
   if ((size(p,1)~=1)& (size(p,2)~=1)) then
      errmsg = msprintf(gettext("%s: p should be a vector"), "qpipopt");
      error(errmsg); 
   end
   
   if (size(LB,1)~=1)& (size(LB,2)~=1) then
      errmsg = msprintf(gettext("%s: Lower Bound should be a vector"), "qpipopt");
      error(errmsg); 
   end
   
   if (size(UB,1)~=1)& (size(UB,2)~=1) then
      errmsg = msprintf(gettext("%s: Upper Bound should be a vector"), "qpipopt");
      error(errmsg); 
   end
   
   if (nbCon) then
        if ((size(conLB,1)~=1)& (size(b,2)~=1)) then
            errmsg = msprintf(gettext("%s: Constraint Lower Bound should be a vector"), "qpipopt");
            error(errmsg); 
        end

        if (size(conUB,1)~=1)& (size(beq,2)~=1) then
            errmsg = msprintf(gettext("%s: Constraint should be a vector"), "qpipopt");
            error(errmsg); 
        end
   end
   
    // Check if the user gives infinity or negative infinity in conLB or conUB
	for i = 1:nbCon
		if (conLB(i) == %inf)
		   	errmsg = msprintf(gettext("%s: Value of Lower Bound can not be infinity"), "qpipopt");
    		error(errmsg); 
  		end	

		if (conUB(i) == -%inf)
		   	errmsg = msprintf(gettext("%s: Value of Upper Bound can not be negative infinity"), "qpipopt");
    		error(errmsg); 
		end	
	end

   [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options);
   
   xopt = xopt';
   exitflag = status;
   output = struct("Iterations"      , []);
   output.Iterations = iter;
   lambda = struct("lower"           , [], ..
                   "upper"           , [], ..
                   "constraint"      , []);
   
   lambda.lower = Zl;
   lambda.upper = Zu;
   lambda.constraint = lmbda;

    select status
    
    case 0 then
        printf("\nOptimal Solution Found.\n");
    case 1 then
        printf("\nMaximum Number of Iterations Exceeded. Output may not be optimal.\n");
    case 2 then
        printf("\nMaximum CPU Time exceeded. Output may not be optimal.\n");
    case 3 then
        printf("\nStop at Tiny Step\n");
    case 4 then
        printf("\nSolved To Acceptable Level\n");
    case 5 then
        printf("\nConverged to a point of local infeasibility.\n");
    case 6 then
        printf("\nStopping optimization at current point as requested by user.\n");
    case 7 then
        printf("\nFeasible point for square problem found.\n");
    case 8 then 
        printf("\nIterates diverging; problem might be unbounded.\n");
    case 9 then
        printf("\nRestoration Failed!\n");
    case 10 then
        printf("\nError in step computation (regularization becomes too large?)!\n");
    case 12 then
        printf("\nProblem has too few degrees of freedom.\n");
    case 13 then
        printf("\nInvalid option thrown back by IPOpt\n");
    case 14 then
        printf("\nNot enough memory.\n");
    case 15 then
        printf("\nINTERNAL ERROR: Unknown SolverReturn value - Notify IPOPT Authors.\n");
    else
        printf("\nInvalid status returned. Notify the Toolbox authors\n");
        break;
    end
    

endfunction