What Is Optimization Toolbox?
What Is Optimization Toolbox? What Is Optimization Toolbox?
lsqlincgiterationsfirstorderoptNumber of PCG iterations(large-scale algorithm only)Measure of first-order optimality(large-scale algorithm only)For large-scale boundconstrained problems, thefirst-order optimality is theinfinity norm of v.*g, wherev isdefined as in “Box Constraints”on page 4-10, and g is thegradient g = C T Cx + C T d (see“Nonlinear Least-Squares” onpage 4-12).OptionsOptimization options used by lsqlin. You can set or change thevalues of these options using the optimset function. Some optionsapply to all algorithms, some are only relevant when you are usingthe large-scale algorithm, and others are only relevant when using themedium-scale algorithm. See “Optimization Options” on page 6-8 fordetailed information.The LargeScale option specifies a preference for which algorithm touse. It is only a preference, because certain conditions must be met touse the large-scale algorithm. For lsqlin, when the problem has onlyupper and lower bounds, i.e., no linearinequalitiesorequalitiesarespecified, the default algorithm is the large-scale method. Otherwisethe medium-scale algorithm is used:LargeScaleUse large-scale algorithm if possible when set to'on'. Use medium-scale algorithm when set to'off'.Medium-Scale and Large-Scale AlgorithmsTheseoptionsareusedbyboththemedium-scale and large-scalealgorithms:8-158
lsqlinDiagnosticsDisplayMaxIterTypicalXDisplay diagnostic information about the functionto be minimized.Level of display. 'off' displays no output; 'final'(default) displays just the final output.Maximum number of iterations allowed.Typical x values.Large-Scale Algorithm OnlyThese options are used only by the large-scale algorithm:8-159
- Page 391 and 392: fsolvePurposeEquationSolve system o
- Page 393 and 394: fsolvefunThe nonlinear system of eq
- Page 395 and 396: fsolvefuncCountalgorithmcgiteration
- Page 397 and 398: fsolvePlotFcnsTolFunPlots various m
- Page 399 and 400: fsolveJacobPatternMaxPCGIterPrecond
- Page 401 and 402: fsolve[x,fval] = fsolve(@myfun,x0,o
- Page 403 and 404: fsolveYoucanformulateandsolvethepro
- Page 405 and 406: fsolveLimitationsThe function to be
- Page 407 and 408: fzeroPurposeSyntaxDescriptionFind r
- Page 409 and 410: fzeroDisplayFunValCheckOutputFcnLev
- Page 411 and 412: fzerowrite an M-file called f.m.fun
- Page 413 and 414: fzmultPurposeSyntaxMultiplication w
- Page 415 and 416: linprogPurposeEquationSolve linear
- Page 417 and 418: linproglambdaoutput-2 No feasible p
- Page 419 and 420: linprogsubject toFirst, enter the c
- Page 421 and 422: linprogDiagnosticsLarge-Scale Optim
- Page 423 and 424: linprogthe primal objective < -1e+1
- Page 425 and 426: lsqcurvefitPurposeEquationSolve non
- Page 427 and 428: lsqcurvefitfunThe function you want
- Page 429 and 430: lsqcurvefitoutputupperUpper bounds
- Page 431 and 432: lsqcurvefitJacobianMaxFunEvalsMaxIt
- Page 433 and 434: lsqcurvefitJacobPatternMaxPCGIterSp
- Page 435 and 436: lsqcurvefitNote that at the time th
- Page 437 and 438: lsqcurvefitof J with many nonzeros,
- Page 439 and 440: lsqlinPurposeEquationSolve constrai
- Page 441: lsqlinlambdaoutput3 Change in the r
- Page 445 and 446: lsqlinPrecondBandWidthUpper bandwid
- Page 447 and 448: lsqlinNotesFor problems with no con
- Page 449 and 450: lsqlinReferences[1] Coleman, T.F. a
- Page 451 and 452: lsqnonlinreturn a vector of values
- Page 453 and 454: lsqnonlinOutputArguments“Function
- Page 455 and 456: lsqnonlinalgorithm. See “Optimiza
- Page 457 and 458: lsqnonlinJacobMultFunction handle f
- Page 459 and 460: lsqnonlinfor(that is, F should have
- Page 461 and 462: lsqnonlinand Requirements on page 2
- Page 463 and 464: lsqnonnegPurposeEquationSolve nonne
- Page 465 and 466: lsqnonneglambdaoutputVector contain
- Page 467 and 468: optimgetPurposeSyntaxDescriptionExa
- Page 469 and 470: optimsetIn the following lists, val
- Page 471 and 472: optimsetLineSearchType'cubicpoly' |
- Page 473 and 474: optimtoolPurposeSyntaxDescriptionTo
- Page 475 and 476: quadprogPurposeEquationSolve quadra
- Page 477 and 478: quadproglambdaoutput3 Change in the
- Page 479 and 480: quadprogLargeScaleUse large-scale a
- Page 481 and 482: quadprogTolPCGTermination tolerance
- Page 483 and 484: quadprogNotesIn general quadprog lo
- Page 485 and 486: quadprogWhen the equality constrain
- Page 487 and 488: IndexIndex ε-Constraint method 3-4
- Page 489 and 490: Indexinfeasible solution warninglin
- Page 491 and 492: Indexdescriptions 6-8possible value
lsqlincgiterationsfirstorderoptNumber of PCG iterations(large-scale algorithm only)Measure of first-order optimality(large-scale algorithm only)For large-scale boundconstrained problems, thefirst-order optimality is theinfinity norm of v.*g, wherev isdefined as in “Box Constraints”on page 4-10, and g is thegradient g = C T Cx + C T d (see“Nonlinear Least-Squares” onpage 4-12).Options<strong>Optimization</strong> options used by lsqlin. You can set or change thevalues of these options using the optimset function. Some optionsapply to all algorithms, some are only relevant when you are usingthe large-scale algorithm, and others are only relevant when using themedium-scale algorithm. See “<strong>Optimization</strong> Options” on page 6-8 fordetailed information.The LargeScale option specifies a preference for which algorithm touse. It is only a preference, because certain conditions must be met touse the large-scale algorithm. For lsqlin, when the problem has onlyupper and lower bounds, i.e., no linearinequalitiesorequalitiesarespecified, the default algorithm is the large-scale method. Otherwisethe medium-scale algorithm is used:LargeScaleUse large-scale algorithm if possible when set to'on'. Use medium-scale algorithm when set to'off'.Medium-Scale and Large-Scale AlgorithmsTheseoptionsareusedbyboththemedium-scale and large-scalealgorithms:8-158