The MOSEK Python optimizer API manual Version 7.0 (Revision 141)
Optimizer API for Python - Documentation - Mosek Optimizer API for Python - Documentation - Mosek
570 APPENDIX D. API CONSTANTS liinfitem.bi clean primal dual iter Number of primal-dual clean iterations performed in the basis identification. liinfitem.bi clean primal dual sub iter Number of primal-dual subproblem clean iterations performed in the basis identification. liinfitem.bi clean primal iter Number of primal clean iterations performed in the basis identification. liinfitem.bi dual iter Number of dual pivots performed in the basis identification. liinfitem.bi primal iter Number of primal pivots performed in the basis identification. liinfitem.intpnt factor num nz Number of non-zeros in factorization. liinfitem.mio intpnt iter Number of interior-point iterations performed by the mixed-integer optimizer. liinfitem.mio simplex iter Number of simplex iterations performed by the mixed-integer optimizer. liinfitem.rd numanz Number of non-zeros in A that is read. liinfitem.rd numqnz Number of Q non-zeros. D.19 Mark mark.lo The lower bound is selected for sensitivity analysis. mark.up The upper bound is selected for sensitivity analysis.
D.20. CONTINUOUS MIXED-INTEGER SOLUTION TYPE 571 D.20 Continuous mixed-integer solution type miocontsoltype.none No interior-point or basic solution are reported when the mixed-integer optimizer is used. miocontsoltype.root The reported interior-point and basic solutions are a solution to the root node problem when mixed-integer optimizer is used. miocontsoltype.itg The reported interior-point and basic solutions are a solution to the problem with all integer variables fixed at the value they have in the integer solution. A solution is only reported in case the problem has a primal feasible solution. miocontsoltype.itg rel In case the problem is primal feasible then the reported interior-point and basic solutions are a solution to the problem with all integer variables fixed at the value they have in the integer solution. If the problem is primal infeasible, then the solution to the root node problem is reported. D.21 Integer restrictions miomode.ignored The integer constraints are ignored and the problem is solved as a continuous problem. miomode.satisfied Integer restrictions should be satisfied. miomode.lazy Integer restrictions should be satisfied if an optimizer is available for the problem. D.22 Mixed-integer node selection types mionodeseltype.free The optimizer decides the node selection strategy. mionodeseltype.first The optimizer employs a depth first node selection strategy. mionodeseltype.best The optimizer employs a best bound node selection strategy.
- Page 541 and 542: 519 rescode.err global inv conic pr
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- Page 547 and 548: 525 rescode.err license no server s
- Page 549 and 550: 527 rescode.err mio no optimizer No
- Page 551 and 552: 529 rescode.err name max len A name
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- Page 567 and 568: Appendix D API constants D.1 Constr
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- Page 591: D.16. INPUT/OUTPUT MODES 569 intpnt
- Page 595 and 596: D.26. OBJECTIVE SENSE TYPES 573 D.2
- Page 597 and 598: D.31. PRESOLVE METHOD. 575 paramete
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- Page 601 and 602: D.42. PROBLEM REFORMULATION. 579 si
- Page 603 and 604: D.46. SOLUTION TYPES 581 solsta.dua
- Page 605 and 606: D.50. STREAM TYPES 583 startpointty
- Page 607 and 608: Appendix E Troubleshooting When cre
- Page 609 and 610: Appendix F Mosek file formats MOSEK
- Page 611 and 612: F.1. THE MPS FILE FORMAT 589 Fields
- Page 613 and 614: F.1. THE MPS FILE FORMAT 591 must b
- Page 615 and 616: F.1. THE MPS FILE FORMAT 593 Constr
- Page 617 and 618: F.1. THE MPS FILE FORMAT 595 v 1 is
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- Page 621 and 622: F.2. THE LP FILE FORMAT 599 minimiz
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- Page 625 and 626: F.2. THE LP FILE FORMAT 603 bounds
- Page 627 and 628: F.3. THE OPF FORMAT 605 iparam.writ
- Page 629 and 630: F.3. THE OPF FORMAT 607 [tag "value
- Page 631 and 632: F.3. THE OPF FORMAT 609 Note that a
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- Page 635 and 636: F.3. THE OPF FORMAT 613 [bounds] [b
- Page 637 and 638: F.4. THE TASK FORMAT 615 This can b
- Page 639 and 640: F.7. THE SOLUTION FILE FORMAT 617 c
- Page 641 and 642: Appendix G Problem analyzer example
570 APPENDIX D. <strong>API</strong> CONSTANTS<br />
liinfitem.bi clean primal dual iter<br />
Number of primal-dual clean iterations performed in the basis identification.<br />
liinfitem.bi clean primal dual sub iter<br />
Number of primal-dual subproblem clean iterations performed in the basis identification.<br />
liinfitem.bi clean primal iter<br />
Number of primal clean iterations performed in the basis identification.<br />
liinfitem.bi dual iter<br />
Number of dual pivots performed in the basis identification.<br />
liinfitem.bi primal iter<br />
Number of primal pivots performed in the basis identification.<br />
liinfitem.intpnt factor num nz<br />
Number of non-zeros in factorization.<br />
liinfitem.mio intpnt iter<br />
Number of interior-point iterations performed by the mixed-integer <strong>optimizer</strong>.<br />
liinfitem.mio simplex iter<br />
Number of simplex iterations performed by the mixed-integer <strong>optimizer</strong>.<br />
liinfitem.rd numanz<br />
Number of non-zeros in A that is read.<br />
liinfitem.rd numqnz<br />
Number of Q non-zeros.<br />
D.19 Mark<br />
mark.lo<br />
<strong>The</strong> lower bound is selected for sensitivity analysis.<br />
mark.up<br />
<strong>The</strong> upper bound is selected for sensitivity analysis.
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