The MOSEK command line tool Version 7.0 (Revision 141)
The MOSEK command line tool. Version 7.0 ... - Documentation The MOSEK command line tool. Version 7.0 ... - Documentation
320 CHAPTER 18. PROBLEM ANALYZER EXAMPLES distrib: A i rows rows% acc% 1 3600 14.20 14.20 2 10803 42.60 56.79 [3, 7] 3995 15.75 72.55 8 6962 27.45 100.00 Column nonzeros, A|j range: min A|j: 0 (0%) max A|j: 61 (0.240536%) distrib: A|j cols cols% acc% 0 3602 11.12 11.12 1 10800 33.33 44.45 2 7200 22.22 66.67 [3, 7] 7279 22.46 89.13 [8, 15] 3521 10.87 100.00 [32, 61] 1 0.00 100.00 3600/3602 empty columns correspond to variables used in conic and/or quadratic constraints only A nonzeros, A(ij) range: min |A(ij)|: 0.00833333 max |A(ij)|: 1.00000 distrib: A(ij) coeffs [0.00833, 0.01) 57280 [0.01, 0.1) 59 [0.1, 1] 36000 ------------------------------------------------------------------------------- Constraint bounds, lb
Bibliography [1] R. Fourer and D. M. Gay and B. W. Kernighan. AMPL. A modeling language for mathematical programming, 2nd edition, 2003. Thomson [2] MOSEK ApS. MOSEK Modeling manual, 2012. Last revised January 31 2013. http://docs.mosek.com/generic/modeling-a4.pdf [3] Andersen, E. D. and Andersen, K. D.. Presolving in linear programming. Math. Programming 2:221-245 [4] Andersen, E. D., Gondzio, J., Mészáros, Cs. and Xu, X.. Implementation of interior point methods for large scale linear programming, Interior-point methods of mathematical programming p. 189-252, 1996. Kluwer Academic Publishers [5] Erling D. Andersen. The homogeneous and self-dual model and algorithm for linear optimization. Technical report TR-1-2009, 2009. MOSEK ApS. http://www.mosek.com/fileadmin/reports/tech/homolo.pdf [6] Andersen, E. D. and Ye, Y.. Combining interior-point and pivoting algorithms. Management Sci. December 12:1719-1731 [7] Ahuja, R. K., Magnanti, T. L. and Orlin, J. B.. Network flows, Optimization, vol. 1 p. 211-369, 1989. North Holland, Amsterdam [8] Andersen, E. D., Roos, C. and Terlaky, T.. On implementing a primal-dual interior-point method for conic quadratic optimization. Math. Programming February 2 [9] Andersen, E. D. and Ye, Y.. A computational study of the homogeneous algorithm for large-scale convex optimization. Computational Optimization and Applications 10:243- 269 [10] Andersen, E. D. and Ye, Y.. On a homogeneous algorithm for the monotone complementarity problem. Math. Programming February 2:375-399 [11] Wolsey, L. A.. Integer programming, 1998. John Wiley and Sons [12] Chvátal, V.. Linear programming, 1983. W.H. Freeman and Company [13] Roos, C., Terlaky, T. and Vial, J. -Ph.. Theory and algorithms for linear optimization: an interior point approach, 1997. John Wiley and Sons, New York 321
- Page 285 and 286: 11.46. SOLUTION TYPES 269 11.46 Sol
- Page 287 and 288: 11.52. INTEGER VALUES 271 11.52 Int
- Page 289 and 290: Chapter 12 MOSEK Command line tool
- Page 291 and 292: 12.3. THE PARAMETER FILE 275 -min F
- Page 293 and 294: Chapter 13 The MPS file format MOSE
- Page 295 and 296: 13.1. MPS FILE STRUCTURE 279 Extens
- Page 297 and 298: 13.1. MPS FILE STRUCTURE 281 [vname
- Page 299 and 300: 13.1. MPS FILE STRUCTURE 283 Field
- Page 301 and 302: 13.1. MPS FILE STRUCTURE 285 Next d
- Page 303 and 304: 13.2. INTEGER VARIABLES 287 13.2 In
- Page 305 and 306: Chapter 14 The LP file format MOSEK
- Page 307 and 308: 14.1. THE SECTIONS 291 x1 * x2 Ther
- Page 309 and 310: 14.2. LP FORMAT PECULIARITIES 293 1
- Page 311 and 312: 14.3. THE STRICT LP FORMAT 295 MSK
- Page 313 and 314: Chapter 15 The OPF format The Optim
- Page 315 and 316: 15.2. THE FILE FORMAT 299 [con ’c
- Page 317 and 318: 15.2. THE FILE FORMAT 301 - ‘NEAR
- Page 319 and 320: 15.4. WRITING OPF FILES FROM MOSEK
- Page 321 and 322: 15.5. EXAMPLES 305 [/hints] [variab
- Page 323 and 324: 15.5. EXAMPLES 307 x1 x2 [/integer]
- Page 325 and 326: Chapter 16 The XML (OSiL) format MO
- Page 327 and 328: Chapter 17 The solution file format
- Page 329 and 330: 17.2. THE INTEGER SOLUTION FILE 313
- Page 331 and 332: Chapter 18 Problem analyzer example
- Page 333 and 334: 18.2. ARKI001 317 2 476 45.42 48.19
- Page 335: 18.4. PROBLEM WITH BOTH LINEAR AND
- Page 339 and 340: Index AMPL outlev, 13 wantsol, 13 a
- Page 341 and 342: INDEX 325 MSK RES ERR FEASREPAIR IN
- Page 343 and 344: INDEX 327 MSK RES ERR MPS NULL VAR
- Page 345 and 346: INDEX 329 MSK RES TRM MAX TIME, 226
320 CHAPTER 18. PROBLEM ANALYZER EXAMPLES<br />
distrib: A i rows rows% acc%<br />
1 3600 14.20 14.20<br />
2 10803 42.60 56.79<br />
[3, 7] 3995 15.75 72.55<br />
8 6962 27.45 100.00<br />
Column nonzeros, A|j<br />
range: min A|j: 0 (0%) max A|j: 61 (0.240536%)<br />
distrib: A|j cols cols% acc%<br />
0 3602 11.12 11.12<br />
1 10800 33.33 44.45<br />
2 7200 22.22 66.67<br />
[3, 7] 7279 22.46 89.13<br />
[8, 15] 3521 10.87 100.00<br />
[32, 61] 1 0.00 100.00<br />
3600/3602 empty columns correspond to variables used in conic<br />
and/or quadratic constraints only<br />
A nonzeros, A(ij)<br />
range: min |A(ij)|: 0.00833333 max |A(ij)|: 1.00000<br />
distrib: A(ij) coeffs<br />
[0.00833, 0.01) 57280<br />
[0.01, 0.1) 59<br />
[0.1, 1] 36000<br />
-------------------------------------------------------------------------------<br />
Constraint bounds, lb
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