The MOSEK command line tool Version 7.0 (Revision 141)

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10 CHAPTER 2. WHAT IS MOSEK 2.1 Interfaces There are several ways to interface with MOSEK: • Files: – MPS format: MOSEK reads the industry standard MPS file format for specifying (mixed integer) linear optimization problems. Moreover an MPS file can also be used to specify quadratic, quadratically constrained, and conic optimization problems. – LP format: MOSEK can read and write the CPLEX LP format with some restrictions. – OPF format: MOSEK also has its own text based format called OPF. The format is closely related to the LP but is much more robust in its specification. • APIs: MOSEK can also invoked from various programming languages. – C/C++, Delphi and similar languages. – C# (and other .NET languages), – Java and – Python Furthermore, the MOSEK Optimization Toolbox for MATLAB allows the MOSEK solvers to be used from Matlab. • Third party modeling languages: – AMPL: A high level modeling language that makes it possible to formulate optimization problems in a language close to the original ”pen and paper” model formulation. See http://www.ampl.com. – GAMS: Another high level modeling language for formulating optimization problems in a clean algebraic way.
Chapter 3 MOSEK and AMPL AMPL is a modeling language for specifying linear and nonlinear optimization models in a natural way. AMPL also makes it easy to solve the problem and e.g. display the solution or part of it. We will not discuss the specifics of the AMPL language here but instead refer the reader to [1], http://ampl.com/BOOK/download.html and the AMPL website http://www.ampl.com. AMPL cannot solve optimization problems by itself but requires a link to an appropriate optimizer such as MOSEK. The MOSEK distribution includes an AMPL link which makes it possible to use MOSEK as an optimizer within AMPL. 3.1 Invoking the AMPL shell The MOSEK distribution by default comes with the AMPL shell installed. To invoke the AMPL shell type: mampl 3.2 Applicability It is possible to specify problems in AMPL that cannot be solved by MOSEK. The optimization problem must be a smooth convex optimization problem as discussed in Section 4.5. 3.3 An example In many instances, you can successfully apply MOSEK simply by specifying the model and data, setting the solver option to MOSEK, and typing solve. First to invoke the AMPL shell type: mampl 11
Page 1 and 2: The MOSEK command line tool. Versio
Page 3 and 4: Contents 1 Changes and new features
Page 5 and 6: CONTENTS v 6.5 Termination criterio
Page 7 and 8: CONTENTS vii 9.1.56 MSK DPAR NONCON
Page 9 and 10: CONTENTS ix 9.2.79 MSK IPAR MIO FEA
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Page 13 and 14: CONTENTS xiii 11.29 Ordering strate
Page 15 and 16: CONTENTS xv 18.2 arki001 . . . . .
Page 17 and 18: Contact information Phone +45 3917
Page 19 and 20: License agreement Before using the
Page 21 and 22: Chapter 1 Changes and new features
Page 23 and 24: 1.4. OPTIMIZATION TOOLBOX FOR MATLA
Page 25: Chapter 2 What is MOSEK MOSEK is a
Page 29 and 30: 3.6. CONSTRAINT AND VARIABLE NAMES
Page 31 and 32: 3.8. HOT-START 15 Linear dependency
Page 33 and 34: 3.10. SENSITIVITY ANALYSIS 17 • .
Page 35 and 36: Chapter 4 Problem formulation and s
Page 37 and 38: 4.1. LINEAR OPTIMIZATION 21 be a pr
Page 39 and 40: 4.2. CONIC QUADRATIC OPTIMIZATION 2
Page 41 and 42: 4.2. CONIC QUADRATIC OPTIMIZATION 2
Page 43 and 44: 4.3. SEMIDEFINITE OPTIMIZATION 27 4
Page 45 and 46: 4.5. GENERAL CONVEX OPTIMIZATION 29
Page 47 and 48: 4.5. GENERAL CONVEX OPTIMIZATION 31
Page 49 and 50: Chapter 5 The optimizers for contin
Page 51 and 52: 5.1. HOW AN OPTIMIZER WORKS 35 5.1.
Page 53 and 54: 5.2. LINEAR OPTIMIZATION 37 5.2.2 T
Page 55 and 56: 5.2. LINEAR OPTIMIZATION 39 Wheneve
Page 57 and 58: 5.2. LINEAR OPTIMIZATION 41 5.2.2.3
Page 59 and 60: 5.2. LINEAR OPTIMIZATION 43 • Rai
Page 61 and 62: 5.5. NONLINEAR CONVEX OPTIMIZATION
Page 63 and 64: 5.6. SOLVING PROBLEMS IN PARALLEL 4
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Page 69 and 70: 6.5. TERMINATION CRITERION 53 The f
Page 71 and 72: 6.7. UNDERSTANDING SOLUTION QUALITY
Page 73 and 74: Chapter 7 The analyzers 7.1 The pro
Page 75 and 76: 7.1. THE PROBLEM ANALYZER 59 Constr
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7.2. ANALYZING INFEASIBLE PROBLEMS
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Chapter 8 Sensitivity analysis 8.1
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8.4. SENSITIVITY ANALYSIS FOR LINEA
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8.5. SENSITIVITY ANALYSIS WITH THE
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8.5. SENSITIVITY ANALYSIS WITH THE
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Chapter 9 Parameters Parameters gro
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81 • MSK SPAR ITR SOL FILE NAME.
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83 • MSK DPAR INTPNT NL TOL REL G
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85 • MSK IPAR LOG MIO. Controls t
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87 • MSK DPAR INTPNT NL MERIT BAL
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89 • MSK IPAR INFEAS PREFER PRIMA
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91 • MSK IPAR SIM SAVE LU. Contro
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9.1. MSKDPARAME: DOUBLE PARAMETERS
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9.2. MSKIPARAME: INTEGER PARAMETERS
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9.3. MSKSPARAME: STRING PARAMETER T
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Chapter 10 Response codes Response
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205 MSK RES ERR CON Q NOT PSD The q
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207 MSK RES ERR GLOBAL INV CONIC PR
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209 MSK RES ERR INV MARKJ Invalid v
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211 MSK RES ERR INVALID FORMAT TYPE
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213 MSK RES ERR LICENSE NO SERVER S
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215 MSK RES ERR MIO NO OPTIMIZER No
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217 MSK RES ERR NAME MAX LEN A name
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219 MSK RES ERR NUMCONLIM Maximum n
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221 MSK RES ERR QCON UPPER TRIANGLE
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223 MSK RES ERR SYM MAT INVALID COL
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225 MSK RES ERR USER NLO FUNC The u
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227 MSK RES WRN ANA ALMOST INT BOUN
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229 MSK RES WRN MIO INFEASIBLE FINA
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231 MSK RES WRN WRITE DISCARDED CFI
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Chapter 11 API constants 11.1 Const
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11.5. PROGRESS CALL-BACK CODES 235
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11.6. TYPES OF CONVEXITY CHECKS. 24
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11.10. DOUBLE INFORMATION ITEMS 245
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11.10. DOUBLE INFORMATION ITEMS 247
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11.11. FEASIBILITY REPAIR TYPES 249
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11.13. INTEGER INFORMATION ITEMS. 2
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11.17. LANGUAGE SELECTION CONSTANTS
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11.22. MIXED-INTEGER NODE SELECTION
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11.29. ORDERING STRATEGIES 261 MSK
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11.34. PROBLEM STATUS KEYS 263 MSK
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11.38. SENSITIVITY TYPES 265 MSK SC
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11.44. SOLUTION ITEMS 267 MSK SIM S
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11.46. SOLUTION TYPES 269 11.46 Sol
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11.52. INTEGER VALUES 271 11.52 Int
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Chapter 12 MOSEK Command line tool
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12.3. THE PARAMETER FILE 275 -min F
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Chapter 13 The MPS file format MOSE
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13.1. MPS FILE STRUCTURE 279 Extens
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13.1. MPS FILE STRUCTURE 281 [vname
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13.1. MPS FILE STRUCTURE 283 Field
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13.1. MPS FILE STRUCTURE 285 Next d
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13.2. INTEGER VARIABLES 287 13.2 In
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Chapter 14 The LP file format MOSEK
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14.1. THE SECTIONS 291 x1 * x2 Ther
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14.2. LP FORMAT PECULIARITIES 293 1
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14.3. THE STRICT LP FORMAT 295 MSK
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Chapter 15 The OPF format The Optim
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15.2. THE FILE FORMAT 299 [con ’c
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15.2. THE FILE FORMAT 301 - ‘NEAR
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15.4. WRITING OPF FILES FROM MOSEK
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15.5. EXAMPLES 305 [/hints] [variab
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15.5. EXAMPLES 307 x1 x2 [/integer]
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Chapter 16 The XML (OSiL) format MO
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Chapter 17 The solution file format
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17.2. THE INTEGER SOLUTION FILE 313
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Chapter 18 Problem analyzer example
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18.2. ARKI001 317 2 476 45.42 48.19
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18.4. PROBLEM WITH BOTH LINEAR AND
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Bibliography [1] R. Fourer and D. M
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Index AMPL outlev, 13 wantsol, 13 a
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INDEX 325 MSK RES ERR FEASREPAIR IN
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INDEX 327 MSK RES ERR MPS NULL VAR
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INDEX 329 MSK RES TRM MAX TIME, 226
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The MOSEK command line tool Version 7.0 (Revision 141)

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