The MOSEK Python optimizer API manual Version 7.0 (Revision 141)

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182 CHAPTER 14. PRIMAL FEASIBILITY REPAIR 0 0.00 Dual basis identification phase terminated. Time: 0.00 Basis identification terminated. Time: 0.00 Interior-point optimizer terminated. Time: 0.00. Optimizer terminated. Time: 0.03 Basic solution summary Problem status : PRIMAL AND DUAL FEASIBLE Solution status : OPTIMAL Primal. obj: 4.2500000000e+001 Viol. con: 1e-013 var: 0e+000 Dual. obj: 4.2500000000e+001 Viol. con: 0e+000 var: 5e-013 Optimal objective value of the penalty problem: 4.250000000000e+001 Repairing bounds. Increasing the upper bound -2.25e+001 on constraint ’c4’ (3) with 1.35e+002. Decreasing the lower bound 6.50e+002 on variable ’x2’ (4) with 2.00e+001. Primal feasibility repair terminated. Optimizer started. Interior-point optimizer started. Presolve started. Presolve terminated. Time: 0.00 Interior-point optimizer terminated. Time: 0.00. Optimizer terminated. Time: 0.00 Interior-point solution summary Problem status : PRIMAL AND DUAL FEASIBLE Solution status : OPTIMAL Primal. obj: -5.6700000000e+003 Viol. con: 0e+000 var: 0e+000 Dual. obj: -5.6700000000e+003 Viol. con: 0e+000 var: 0e+000 Basic solution summary Problem status : PRIMAL AND DUAL FEASIBLE Solution status : OPTIMAL Primal. obj: -5.6700000000e+003 Viol. con: 0e+000 var: 0e+000 Dual. obj: -5.6700000000e+003 Viol. con: 0e+000 var: 0e+000 Optimizer summary Optimizer - time: 0.00 Interior-point - iterations : 0 time: 0.00 Basis identification - time: 0.00 Primal - iterations : 0 time: 0.00 Dual - iterations : 0 time: 0.00 Clean primal - iterations : 0 time: 0.00 Clean dual - iterations : 0 time: 0.00 Clean primal-dual - iterations : 0 time: 0.00 Simplex - time: 0.00 Primal simplex - iterations : 0 time: 0.00 Dual simplex - iterations : 0 time: 0.00 Primal-dual simplex - iterations : 0 time: 0.00 Mixed integer - relaxations: 0 time: 0.00 reports the optimal repair. In this case it is to increase the upper bound on constraint c4 by 1.35e2 and decrease the lower bound on variable x2 by 20.
14.3. FEASIBILITY REPAIR IN MOSEK 183 14.3.2 Feasibility repair using the API The function Task.primalrepair can be used to repair an infeasible problem. function Task.primalrepair can be seen in the reference. Details about the 1 # 14.3.2.1 An example Consider once again the example (14.7) then [ feasrepairex1.py ] 2 # Copyright: Copyright (c) MOSEK ApS, Denmark. All rights reserved. 3 # 4 # File: feasrepairex1.py 5 # 6 # Purpose: To demonstrate how to use the MSK relaxprimal function to 7 # locate the cause of an infeasibility. 8 # 9 # Syntax: On command line 10 # python feasrepairex1.py feasrepair.lp 11 # feasrepair.lp is located in mosek\\tools\examples. 12 13 14 import sys 15 import mosek 16 17 # Since the actual value of Infinity is ignores, we define it solely 18 # for symbolic purposes: 19 inf = 0.0 20 21 # Define a stream printer to grab output from MOSEK 22 def streamprinter(text): 23 sys.stdout.write(text) 24 sys.stdout.flush() 25 26 def main (inputfile): 27 # Make a MOSEK environment 28 with mosek.Env () as env: 29 with env.Task(0,0) as task: 30 # Attach a printer to the task 31 task.set Stream (mosek.streamtype.log, streamprinter) 32 33 # Read data 34 task.readdata(inputfile) 35 36 task.putintparam(mosek.iparam.log feas repair,3) 37 38 task.primalrepair(None,None,None,None) 39 40 sum viol = task.getdouinf(mosek.dinfitem.primal repair penalty obj) 41 print ("Minimized sum of violations = %e" % sum viol) 42 43 task.optimize() 44 45 task.solutionsummary(mosek.streamtype.msg) 46
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The MOSEK Python optimizer API manu
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Contents 1 Changes and new features
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CONTENTS v 8 A case study 97 8.1 Po
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CONTENTS vii 14.2.1 Caveats . . . .
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CONTENTS ix A.2.70 Task.getdviolvar
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CONTENTS xi A.2.162Task.isdouparnam
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CONTENTS xiii A.2.254Task.readparam
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CONTENTS xv B.1.45 dparam.mio near
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CONTENTS xvii B.2.68 iparam.log sim
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CONTENTS xix B.2.160iparam.sim refa
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CONTENTS xxi D.18 Long integer info
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Contact information Phone +45 3917
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License agreement Before using the
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Chapter 1 Changes and new features
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1.4. API CHANGES 7 1.3.3 Mixed-inte
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1.10. SUMMARY OF API CHANGES 9 •
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Chapter 2 About this manual This ma
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Chapter 3 Getting support and help
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Chapter 4 Testing installation and
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Chapter 5 Basic API tutorial In thi
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5.1. THE BASICS 23 5 # 6 # Purpose:
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5.2. LINEAR OPTIMIZATION 25 and the
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5.2. LINEAR OPTIMIZATION 27 Load a
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5.2. LINEAR OPTIMIZATION 29 Optimiz
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5.2. LINEAR OPTIMIZATION 31 88 task
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5.2. LINEAR OPTIMIZATION 33 51 mose
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5.3. CONIC QUADRATIC OPTIMIZATION 3
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5.3. CONIC QUADRATIC OPTIMIZATION 3
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5.4. SEMIDEFINITE OPTIMIZATION 39 m
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5.4. SEMIDEFINITE OPTIMIZATION 41 4
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5.4. SEMIDEFINITE OPTIMIZATION 43 1
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5.5. QUADRATIC OPTIMIZATION 45 with
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5.5. QUADRATIC OPTIMIZATION 47 68 #
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5.5. QUADRATIC OPTIMIZATION 49 5.5.
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5.5. QUADRATIC OPTIMIZATION 51 81 a
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5.6. THE SOLUTION SUMMARY 53 • Th
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5.7. INTEGER OPTIMIZATION 55 21 # f
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5.7. INTEGER OPTIMIZATION 57 137 sy
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5.8. THE SOLUTION SUMMARY FOR MIXED
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5.9. RESPONSE HANDLING 61 Note that
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5.10. PROBLEM MODIFICATION AND REOP
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5.10. PROBLEM MODIFICATION AND REOP
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5.11. SOLUTION ANALYSIS 67 151 # Pu
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5.13. CONVENTIONS EMPLOYED IN THE A
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Chapter 6 Nonlinear API tutorial Th
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6.1. SEPARABLE CONVEX (SCOPT) INTER
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Chapter 7 Advanced API tutorial Thi
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7.1. THE PROGRESS CALL-BACK 87 71 p
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7.2. SOLVING LINEAR SYSTEMS INVOLVI
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Chapter 8 A case study 8.1 Portfoli
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8.1. PORTFOLIO OPTIMIZATION 99 e T
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8.1. PORTFOLIO OPTIMIZATION 101 is
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8.1. PORTFOLIO OPTIMIZATION 103 15
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8.1. PORTFOLIO OPTIMIZATION 107 8.1
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8.1. PORTFOLIO OPTIMIZATION 111 z j
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8.1. PORTFOLIO OPTIMIZATION 113 Var
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Chapter 9 Usage guidelines The purp
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9.3. WRITING TASK DATA TO A FILE 12
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Chapter 10 Problem formulation and
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10.1. LINEAR OPTIMIZATION 125 be a
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10.2. CONIC QUADRATIC OPTIMIZATION
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10.2. CONIC QUADRATIC OPTIMIZATION
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Page 159 and 160: 11.1. HOW AN OPTIMIZER WORKS 137 11
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Page 163 and 164: 11.2. LINEAR OPTIMIZATION 141 Whene
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Page 177 and 178: Chapter 12 The optimizers for mixed
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Page 181 and 182: 12.5. TERMINATION CRITERION 159 •
Page 183 and 184: 12.7. UNDERSTANDING SOLUTION QUALIT
Page 185 and 186: Chapter 13 The analyzers 13.1 The p
Page 187 and 188: 13.1. THE PROBLEM ANALYZER 165 Cons
Page 189 and 190: 13.2. ANALYZING INFEASIBLE PROBLEMS
Page 199 and 200: Chapter 14 Primal feasibility repai
Page 201 and 202: 14.2. AUTOMATIC REPAIR 179 One way
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Page 221 and 222: Appendix A API reference This chapt
Page 223 and 224: 201 • Task.relaxprimal Obtain inf
Page 225 and 226: A.1. EXCEPTIONS 203 • Task.putvar
Page 227 and 228: A.2. CLASS TASK 205 Arguments which
Page 229 and 230: A.2. CLASS TASK 207 See also • Ro
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A.2. CLASS TASK 233 conetype : cone
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A.2. CLASS TASK 235 Description: Ob
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A.2. CLASS TASK 237 sub : int[] Ind
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A.2. CLASS TASK 239 A.2.64 Task.get
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A.2. CLASS TASK 241 Computes the vi
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A.2. CLASS TASK 253 k : int Index o
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A.2. CLASS TASK 255 A.2.103 Task.ge
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A.2. CLASS TASK 257 normalize : int
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A.2. CLASS TASK 259 Description: Le
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A.2. CLASS TASK 261 max(l x j τ
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A.2. CLASS TASK 265 last : int Last
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A.2. CLASS TASK 269 Arguments snx :
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A.2. CLASS TASK 271 slc : double[]
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A.2. CLASS TASK 273 Arguments accmo
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A.2. CLASS TASK 277 last : int Valu
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A.2. CLASS TASK 279 subi : int[] Ro
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A.2. CLASS TASK 283 Arguments taskn
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A.2. CLASS TASK 287 vartype : varia
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A.2. CLASS TASK 289 whichsol : solt
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A.2. CLASS TASK 293 A.2.162 Task.is
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A.2. CLASS TASK 295 whichstream : s
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A.2. CLASS TASK 297 A.2.170 Task.pr
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A.2. CLASS TASK 299 markj : mark Th
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A.2. CLASS TASK 301 Prints a part o
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A.2. CLASS TASK 303 A.2.175 Task.pu
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A.2. CLASS TASK 305 j : int Index o
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A.2. CLASS TASK 309 Description: Th
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A.2. CLASS TASK 313 Changes the bou
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A.2. CLASS TASK 315 Modifies one li
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A.2. CLASS TASK 317 bkc : boundkey
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A.2. CLASS TASK 319 Arguments j : i
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A.2. CLASS TASK 321 parvalue : int
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A.2. CLASS TASK 325 Sets a string p
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A.2. CLASS TASK 327 Description: Re
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A.2. CLASS TASK 329 qosubj : int[]
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A.2. CLASS TASK 331 Sets the status
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A.2. CLASS TASK 335 Arguments sux :
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A.2. CLASS TASK 337 y : double[] Ve
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A.2. CLASS TASK 341 last : int Last
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A.2. CLASS TASK 343 See also • Ta
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A.2. CLASS TASK 347 Description: Se
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A.2. CLASS TASK 349 Sets a slice of
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A.2. CLASS TASK 351 A.2.254 Task.re
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A.2. CLASS TASK 353 wux : double[]
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A.2. CLASS TASK 355 See also • Ta
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A.2. CLASS TASK 357 isdef : int Is
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A.2. CLASS TASK 359 A.2.269 Task.st
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A.2. CLASS TASK 361 Description: Wr
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A.3. CLASS ENV 363 A.2.278 Task.wri
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A.3. CLASS ENV 365 Arguments code :
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A.3. CLASS ENV 367 Arguments keepdl
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A.4. CALLBACK FUNCTIONS AND RELATED
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A.6. ALL FUNCTIONS BY NAME 371 Task
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Appendix B Parameters Parameters gr
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391 • iparam.log file. If turned
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393 • dparam.intpnt nl tol rel st
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395 • iparam.mio construct sol. C
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397 • dparam.intpnt nl tol mu red
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399 • iparam.mio mode. Turns on/o
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401 • iparam.sim solve form. Cont
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B.1. DPARAM: DOUBLE PARAMETERS 403
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B.2. IPARAM: INTEGER PARAMETERS 427
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B.3. SPARAM: STRING PARAMETER TYPES
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Appendix C Response codes Response
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517 rescode.err con q not psd The q
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519 rescode.err global inv conic pr
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521 rescode.err inv markj Invalid v
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523 rescode.err invalid format type
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525 rescode.err license no server s
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527 rescode.err mio no optimizer No
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529 rescode.err name max len A name
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531 rescode.err numconlim Maximum n
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533 rescode.err qcon upper triangle
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535 rescode.err sym mat invalid col
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537 rescode.err user nlo func The u
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539 rescode.wrn ana almost int boun
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541 rescode.wrn mio infeasible fina
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543 rescode.wrn write discarded cfi
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Appendix D API constants D.1 Constr
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D.5. PROGRESS CALL-BACK CODES 547 c
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D.6. TYPES OF CONVEXITY CHECKS. 555
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D.10. DOUBLE INFORMATION ITEMS 557
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D.10. DOUBLE INFORMATION ITEMS 559
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D.11. FEASIBILITY REPAIR TYPES 561
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D.13. INTEGER INFORMATION ITEMS. 56
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D.16. INPUT/OUTPUT MODES 569 intpnt
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D.20. CONTINUOUS MIXED-INTEGER SOLU
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D.26. OBJECTIVE SENSE TYPES 573 D.2
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D.31. PRESOLVE METHOD. 575 paramete
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D.35. RESPONSE CODE TYPE 577 D.35 R
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D.42. PROBLEM REFORMULATION. 579 si
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D.46. SOLUTION TYPES 581 solsta.dua
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D.50. STREAM TYPES 583 startpointty
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Appendix E Troubleshooting When cre
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Appendix F Mosek file formats MOSEK
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F.1. THE MPS FILE FORMAT 589 Fields
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F.1. THE MPS FILE FORMAT 591 must b
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F.1. THE MPS FILE FORMAT 593 Constr
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F.1. THE MPS FILE FORMAT 595 v 1 is
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F.1. THE MPS FILE FORMAT 597 Please
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F.2. THE LP FILE FORMAT 599 minimiz
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F.2. THE LP FILE FORMAT 601 st defi
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F.2. THE LP FILE FORMAT 603 bounds
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F.3. THE OPF FORMAT 605 iparam.writ
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F.3. THE OPF FORMAT 607 [tag "value
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F.3. THE OPF FORMAT 609 Note that a
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F.3. THE OPF FORMAT 611 F.3.2.3 Nam
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F.3. THE OPF FORMAT 613 [bounds] [b
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F.4. THE TASK FORMAT 615 This can b
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F.7. THE SOLUTION FILE FORMAT 617 c
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Appendix G Problem analyzer example
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G.2. ARKI001 621 2 476 45.42 48.19
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G.4. PROBLEM WITH BOTH LINEAR AND C
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Bibliography [1] Chvátal, V.. Line
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Index analyzenames (Task method), 2
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INDEX 629 getpcni (Task method), 25
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INDEX 631 putbarablocktriplet (Task
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INDEX 633 rescode.err inv numj, 521
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INDEX 635 rescode.err sen bound inv
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