Actual source code: viss.c
petsc-3.10.5 2019-03-28
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      2:  #include <../src/snes/impls/vi/ss/vissimpl.h>

      4: /*
      5:   SNESVIComputeMeritFunction - Evaluates the merit function for the mixed complementarity problem.

      7:   Input Parameter:
      8: . phi - the semismooth function

     10:   Output Parameter:
     11: . merit - the merit function
     12: . phinorm - ||phi||

     14:   Notes:
     15:   The merit function for the mixed complementarity problem is defined as
     16:      merit = 0.5*phi^T*phi
     17: */
     18: static PetscErrorCode SNESVIComputeMeritFunction(Vec phi, PetscReal *merit,PetscReal *phinorm)
     19: {

     23:   VecNormBegin(phi,NORM_2,phinorm);
     24:   VecNormEnd(phi,NORM_2,phinorm);

     26:   *merit = 0.5*(*phinorm)*(*phinorm);
     27:   return(0);
     28: }

     30: PETSC_STATIC_INLINE PetscScalar Phi(PetscScalar a,PetscScalar b)
     31: {
     32:   return a + b - PetscSqrtScalar(a*a + b*b);
     33: }

     35: PETSC_STATIC_INLINE PetscScalar DPhi(PetscScalar a,PetscScalar b)
     36: {
     37:   if ((PetscAbsScalar(a) >= 1.e-6) || (PetscAbsScalar(b) >= 1.e-6)) return 1.0 - a/ PetscSqrtScalar(a*a + b*b);
     38:   else return .5;
     39: }

     41: /*
     42:    SNESVIComputeFunction - Reformulates a system of nonlinear equations in mixed complementarity form to a system of nonlinear equations in semismooth form.

     44:    Input Parameters:
     45: .  snes - the SNES context
     46: .  X - current iterate
     47: .  functx - user defined function context

     49:    Output Parameters:
     50: .  phi - Semismooth function

     52: */
     53: static PetscErrorCode SNESVIComputeFunction(SNES snes,Vec X,Vec phi,void *functx)
     54: {
     55:   PetscErrorCode    ierr;
     56:   SNES_VINEWTONSSLS *vi = (SNES_VINEWTONSSLS*)snes->data;
     57:   Vec               Xl  = snes->xl,Xu = snes->xu,F = snes->vec_func;
     58:   PetscScalar       *phi_arr,*f_arr,*l,*u;
     59:   const PetscScalar *x_arr;
     60:   PetscInt          i,nlocal;

     63:   (*vi->computeuserfunction)(snes,X,F,functx);
     64:   VecGetLocalSize(X,&nlocal);
     65:   VecGetArrayRead(X,&x_arr);
     66:   VecGetArray(F,&f_arr);
     67:   VecGetArray(Xl,&l);
     68:   VecGetArray(Xu,&u);
     69:   VecGetArray(phi,&phi_arr);

     71:   for (i=0; i < nlocal; i++) {
     72:     if ((PetscRealPart(l[i]) <= PETSC_NINFINITY) && (PetscRealPart(u[i]) >= PETSC_INFINITY)) { /* no constraints on variable */
     73:       phi_arr[i] = f_arr[i];
     74:     } else if (PetscRealPart(l[i]) <= PETSC_NINFINITY) {                      /* upper bound on variable only */
     75:       phi_arr[i] = -Phi(u[i] - x_arr[i],-f_arr[i]);
     76:     } else if (PetscRealPart(u[i]) >= PETSC_INFINITY) {                       /* lower bound on variable only */
     77:       phi_arr[i] = Phi(x_arr[i] - l[i],f_arr[i]);
     78:     } else if (l[i] == u[i]) {
     79:       phi_arr[i] = l[i] - x_arr[i];
     80:     } else {                                                /* both bounds on variable */
     81:       phi_arr[i] = Phi(x_arr[i] - l[i],-Phi(u[i] - x_arr[i],-f_arr[i]));
     82:     }
     83:   }

     85:   VecRestoreArrayRead(X,&x_arr);
     86:   VecRestoreArray(F,&f_arr);
     87:   VecRestoreArray(Xl,&l);
     88:   VecRestoreArray(Xu,&u);
     89:   VecRestoreArray(phi,&phi_arr);
     90:   return(0);
     91: }

     93: /*
     94:    SNESVIComputeBsubdifferentialVectors - Computes the diagonal shift (Da) and row scaling (Db) vectors needed for the
     95:                                           the semismooth jacobian.
     96: */
     97: PetscErrorCode SNESVIComputeBsubdifferentialVectors(SNES snes,Vec X,Vec F,Mat jac,Vec Da,Vec Db)
     98: {
    100:   PetscScalar    *l,*u,*x,*f,*da,*db,da1,da2,db1,db2;
    101:   PetscInt       i,nlocal;

    104:   VecGetArray(X,&x);
    105:   VecGetArray(F,&f);
    106:   VecGetArray(snes->xl,&l);
    107:   VecGetArray(snes->xu,&u);
    108:   VecGetArray(Da,&da);
    109:   VecGetArray(Db,&db);
    110:   VecGetLocalSize(X,&nlocal);

    112:   for (i=0; i< nlocal; i++) {
    113:     if ((PetscRealPart(l[i]) <= PETSC_NINFINITY) && (PetscRealPart(u[i]) >= PETSC_INFINITY)) { /* no constraints on variable */
    114:       da[i] = 0;
    115:       db[i] = 1;
    116:     } else if (PetscRealPart(l[i]) <= PETSC_NINFINITY) {                     /* upper bound on variable only */
    117:       da[i] = DPhi(u[i] - x[i], -f[i]);
    118:       db[i] = DPhi(-f[i],u[i] - x[i]);
    119:     } else if (PetscRealPart(u[i]) >= PETSC_INFINITY) {                      /* lower bound on variable only */
    120:       da[i] = DPhi(x[i] - l[i], f[i]);
    121:       db[i] = DPhi(f[i],x[i] - l[i]);
    122:     } else if (l[i] == u[i]) {                              /* fixed variable */
    123:       da[i] = 1;
    124:       db[i] = 0;
    125:     } else {                                                /* upper and lower bounds on variable */
    126:       da1   = DPhi(x[i] - l[i], -Phi(u[i] - x[i], -f[i]));
    127:       db1   = DPhi(-Phi(u[i] - x[i], -f[i]),x[i] - l[i]);
    128:       da2   = DPhi(u[i] - x[i], -f[i]);
    129:       db2   = DPhi(-f[i],u[i] - x[i]);
    130:       da[i] = da1 + db1*da2;
    131:       db[i] = db1*db2;
    132:     }
    133:   }

    135:   VecRestoreArray(X,&x);
    136:   VecRestoreArray(F,&f);
    137:   VecRestoreArray(snes->xl,&l);
    138:   VecRestoreArray(snes->xu,&u);
    139:   VecRestoreArray(Da,&da);
    140:   VecRestoreArray(Db,&db);
    141:   return(0);
    142: }

    144: /*
    145:    SNESVIComputeJacobian - Computes the jacobian of the semismooth function.The Jacobian for the semismooth function is an element of the B-subdifferential of the Fischer-Burmeister function for complementarity problems.

    147:    Input Parameters:
    148: .  Da       - Diagonal shift vector for the semismooth jacobian.
    149: .  Db       - Row scaling vector for the semismooth jacobian.

    151:    Output Parameters:
    152: .  jac      - semismooth jacobian
    153: .  jac_pre  - optional preconditioning matrix

    155:    Notes:
    156:    The semismooth jacobian matrix is given by
    157:    jac = Da + Db*jacfun
    158:    where Db is the row scaling matrix stored as a vector,
    159:          Da is the diagonal perturbation matrix stored as a vector
    160:    and   jacfun is the jacobian of the original nonlinear function.
    161: */
    162: PetscErrorCode SNESVIComputeJacobian(Mat jac, Mat jac_pre,Vec Da, Vec Db)
    163: {

    166:   /* Do row scaling  and add diagonal perturbation */
    167:   MatDiagonalScale(jac,Db,NULL);
    168:   MatDiagonalSet(jac,Da,ADD_VALUES);
    169:   if (jac != jac_pre) { /* If jac and jac_pre are different */
    170:     MatDiagonalScale(jac_pre,Db,NULL);
    171:     MatDiagonalSet(jac_pre,Da,ADD_VALUES);
    172:   }
    173:   return(0);
    174: }

    176: /*
    177:    SNESVIComputeMeritFunctionGradient - Computes the gradient of the merit function psi.

    179:    Input Parameters:
    180:    phi - semismooth function.
    181:    H   - semismooth jacobian

    183:    Output Parameters:
    184:    dpsi - merit function gradient

    186:    Notes:
    187:   The merit function gradient is computed as follows
    188:         dpsi = H^T*phi
    189: */
    190: PetscErrorCode SNESVIComputeMeritFunctionGradient(Mat H, Vec phi, Vec dpsi)
    191: {

    195:   MatMultTranspose(H,phi,dpsi);
    196:   return(0);
    197: }

    201: /*
    202:    SNESSolve_VINEWTONSSLS - Solves the complementarity problem with a semismooth Newton
    203:    method using a line search.

    205:    Input Parameters:
    206: .  snes - the SNES context

    208:    Application Interface Routine: SNESSolve()

    210:    Notes:
    211:    This implements essentially a semismooth Newton method with a
    212:    line search. The default line search does not do any line search
    213:    but rather takes a full Newton step.

    215:    Developer Note: the code in this file should be slightly modified so that this routine need not exist and the SNESSolve_NEWTONLS() routine is called directly with the appropriate wrapped function and Jacobian evaluations

    217: */
    218: PetscErrorCode SNESSolve_VINEWTONSSLS(SNES snes)
    219: {
    220:   SNES_VINEWTONSSLS    *vi = (SNES_VINEWTONSSLS*)snes->data;
    221:   PetscErrorCode       ierr;
    222:   PetscInt             maxits,i,lits;
    223:   SNESLineSearchReason lssucceed;
    224:   PetscReal            gnorm,xnorm=0,ynorm;
    225:   Vec                  Y,X,F;
    226:   KSPConvergedReason   kspreason;
    227:   DM                   dm;
    228:   DMSNES               sdm;

    231:   SNESGetDM(snes,&dm);
    232:   DMGetDMSNES(dm,&sdm);

    234:   vi->computeuserfunction   = sdm->ops->computefunction;
    235:   sdm->ops->computefunction = SNESVIComputeFunction;

    237:   snes->numFailures            = 0;
    238:   snes->numLinearSolveFailures = 0;
    239:   snes->reason                 = SNES_CONVERGED_ITERATING;

    241:   maxits = snes->max_its;               /* maximum number of iterations */
    242:   X      = snes->vec_sol;               /* solution vector */
    243:   F      = snes->vec_func;              /* residual vector */
    244:   Y      = snes->work[0];               /* work vectors */

    246:   PetscObjectSAWsTakeAccess((PetscObject)snes);
    247:   snes->iter = 0;
    248:   snes->norm = 0.0;
    249:   PetscObjectSAWsGrantAccess((PetscObject)snes);

    251:   SNESVIProjectOntoBounds(snes,X);
    252:   SNESComputeFunction(snes,X,vi->phi);
    253:   if (snes->domainerror) {
    254:     snes->reason              = SNES_DIVERGED_FUNCTION_DOMAIN;
    255:     sdm->ops->computefunction = vi->computeuserfunction;
    256:     return(0);
    257:   }
    258:   /* Compute Merit function */
    259:   SNESVIComputeMeritFunction(vi->phi,&vi->merit,&vi->phinorm);

    261:   VecNormBegin(X,NORM_2,&xnorm);        /* xnorm <- ||x||  */
    262:   VecNormEnd(X,NORM_2,&xnorm);
    263:   SNESCheckFunctionNorm(snes,vi->merit);

    265:   PetscObjectSAWsTakeAccess((PetscObject)snes);
    266:   snes->norm = vi->phinorm;
    267:   PetscObjectSAWsGrantAccess((PetscObject)snes);
    268:   SNESLogConvergenceHistory(snes,vi->phinorm,0);
    269:   SNESMonitor(snes,0,vi->phinorm);

    271:   /* test convergence */
    272:   (*snes->ops->converged)(snes,0,0.0,0.0,vi->phinorm,&snes->reason,snes->cnvP);
    273:   if (snes->reason) {
    274:     sdm->ops->computefunction = vi->computeuserfunction;
    275:     return(0);
    276:   }

    278:   for (i=0; i<maxits; i++) {

    280:     /* Call general purpose update function */
    281:     if (snes->ops->update) {
    282:       (*snes->ops->update)(snes, snes->iter);
    283:     }

    285:     /* Solve J Y = Phi, where J is the semismooth jacobian */

    287:     /* Get the jacobian -- note that the function must be the original function for snes_fd and snes_fd_color to work for this*/
    288:     sdm->ops->computefunction = vi->computeuserfunction;
    289:     SNESComputeJacobian(snes,X,snes->jacobian,snes->jacobian_pre);
    290:     sdm->ops->computefunction = SNESVIComputeFunction;

    292:     /* Get the diagonal shift and row scaling vectors */
    293:     SNESVIComputeBsubdifferentialVectors(snes,X,F,snes->jacobian,vi->Da,vi->Db);
    294:     /* Compute the semismooth jacobian */
    295:     SNESVIComputeJacobian(snes->jacobian,snes->jacobian_pre,vi->Da,vi->Db);
    296:     /* Compute the merit function gradient */
    297:     SNESVIComputeMeritFunctionGradient(snes->jacobian,vi->phi,vi->dpsi);
    298:     KSPSetOperators(snes->ksp,snes->jacobian,snes->jacobian_pre);
    299:     KSPSolve(snes->ksp,vi->phi,Y);
    300:     KSPGetConvergedReason(snes->ksp,&kspreason);

    302:     if (kspreason < 0) {
    303:       if (++snes->numLinearSolveFailures >= snes->maxLinearSolveFailures) {
    304:         PetscInfo2(snes,"iter=%D, number linear solve failures %D greater than current SNES allowed, stopping solve\n",snes->iter,snes->numLinearSolveFailures);
    305:         snes->reason = SNES_DIVERGED_LINEAR_SOLVE;
    306:         break;
    307:       }
    308:     }
    309:     KSPGetIterationNumber(snes->ksp,&lits);
    310:     snes->linear_its += lits;
    311:     PetscInfo2(snes,"iter=%D, linear solve iterations=%D\n",snes->iter,lits);
    312:     /*
    313:     if (snes->ops->precheck) {
    314:       PetscBool changed_y = PETSC_FALSE;
    315:       (*snes->ops->precheck)(snes,X,Y,snes->precheck,&changed_y);
    316:     }

    318:     if (PetscLogPrintInfo) {
    319:       SNESVICheckResidual_Private(snes,snes->jacobian,F,Y,G,W);
    320:     }
    321:     */
    322:     /* Compute a (scaled) negative update in the line search routine:
    323:          Y <- X - lambda*Y
    324:        and evaluate G = function(Y) (depends on the line search).
    325:     */
    326:     VecCopy(Y,snes->vec_sol_update);
    327:     ynorm = 1; gnorm = vi->phinorm;
    328:     SNESLineSearchApply(snes->linesearch, X, vi->phi, &gnorm, Y);
    329:     SNESLineSearchGetReason(snes->linesearch, &lssucceed);
    330:     SNESLineSearchGetNorms(snes->linesearch, &xnorm, &gnorm, &ynorm);
    331:     PetscInfo4(snes,"fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, lssucceed=%d\n",(double)vi->phinorm,(double)gnorm,(double)ynorm,(int)lssucceed);
    332:     if (snes->reason == SNES_DIVERGED_FUNCTION_COUNT) break;
    333:     if (snes->domainerror) {
    334:       snes->reason              = SNES_DIVERGED_FUNCTION_DOMAIN;
    335:       sdm->ops->computefunction = vi->computeuserfunction;
    336:       return(0);
    337:     }
    338:     if (lssucceed) {
    339:       if (++snes->numFailures >= snes->maxFailures) {
    340:         PetscBool ismin;
    341:         snes->reason = SNES_DIVERGED_LINE_SEARCH;
    342:         SNESVICheckLocalMin_Private(snes,snes->jacobian,vi->phi,X,gnorm,&ismin);
    343:         if (ismin) snes->reason = SNES_DIVERGED_LOCAL_MIN;
    344:         break;
    345:       }
    346:     }
    347:     /* Update function and solution vectors */
    348:     vi->phinorm = gnorm;
    349:     vi->merit   = 0.5*vi->phinorm*vi->phinorm;
    350:     /* Monitor convergence */
    351:     PetscObjectSAWsTakeAccess((PetscObject)snes);
    352:     snes->iter = i+1;
    353:     snes->norm = vi->phinorm;
    354:     PetscObjectSAWsGrantAccess((PetscObject)snes);
    355:     SNESLogConvergenceHistory(snes,snes->norm,lits);
    356:     SNESMonitor(snes,snes->iter,snes->norm);
    357:     /* Test for convergence, xnorm = || X || */
    358:     if (snes->ops->converged != SNESConvergedSkip) { VecNorm(X,NORM_2,&xnorm); }
    359:     (*snes->ops->converged)(snes,snes->iter,xnorm,ynorm,vi->phinorm,&snes->reason,snes->cnvP);
    360:     if (snes->reason) break;
    361:   }
    362:   if (i == maxits) {
    363:     PetscInfo1(snes,"Maximum number of iterations has been reached: %D\n",maxits);
    364:     if (!snes->reason) snes->reason = SNES_DIVERGED_MAX_IT;
    365:   }
    366:   sdm->ops->computefunction = vi->computeuserfunction;
    367:   return(0);
    368: }

    370: /* -------------------------------------------------------------------------- */
    371: /*
    372:    SNESSetUp_VINEWTONSSLS - Sets up the internal data structures for the later use
    373:    of the SNES nonlinear solver.

    375:    Input Parameter:
    376: .  snes - the SNES context

    378:    Application Interface Routine: SNESSetUp()

    380:    Notes:
    381:    For basic use of the SNES solvers, the user need not explicitly call
    382:    SNESSetUp(), since these actions will automatically occur during
    383:    the call to SNESSolve().
    384:  */
    385: PetscErrorCode SNESSetUp_VINEWTONSSLS(SNES snes)
    386: {
    387:   PetscErrorCode    ierr;
    388:   SNES_VINEWTONSSLS *vi = (SNES_VINEWTONSSLS*) snes->data;

    391:   SNESSetUp_VI(snes);
    392:   VecDuplicate(snes->vec_sol, &vi->dpsi);
    393:   VecDuplicate(snes->vec_sol, &vi->phi);
    394:   VecDuplicate(snes->vec_sol, &vi->Da);
    395:   VecDuplicate(snes->vec_sol, &vi->Db);
    396:   VecDuplicate(snes->vec_sol, &vi->z);
    397:   VecDuplicate(snes->vec_sol, &vi->t);
    398:   return(0);
    399: }
    400: /* -------------------------------------------------------------------------- */
    401: PetscErrorCode SNESReset_VINEWTONSSLS(SNES snes)
    402: {
    403:   SNES_VINEWTONSSLS *vi = (SNES_VINEWTONSSLS*) snes->data;
    404:   PetscErrorCode    ierr;

    407:   SNESReset_VI(snes);
    408:   VecDestroy(&vi->dpsi);
    409:   VecDestroy(&vi->phi);
    410:   VecDestroy(&vi->Da);
    411:   VecDestroy(&vi->Db);
    412:   VecDestroy(&vi->z);
    413:   VecDestroy(&vi->t);
    414:   return(0);
    415: }

    417: /* -------------------------------------------------------------------------- */
    418: /*
    419:    SNESSetFromOptions_VINEWTONSSLS - Sets various parameters for the SNESVI method.

    421:    Input Parameter:
    422: .  snes - the SNES context

    424:    Application Interface Routine: SNESSetFromOptions()
    425: */
    426: static PetscErrorCode SNESSetFromOptions_VINEWTONSSLS(PetscOptionItems *PetscOptionsObject,SNES snes)
    427: {
    429:   SNESLineSearch linesearch;

    432:   SNESSetFromOptions_VI(PetscOptionsObject,snes);
    433:   PetscOptionsHead(PetscOptionsObject,"SNES semismooth method options");
    434:   PetscOptionsTail();
    435:   /* set up the default line search */
    436:   if (!snes->linesearch) {
    437:     SNESGetLineSearch(snes, &linesearch);
    438:     SNESLineSearchSetType(linesearch, SNESLINESEARCHBT);
    439:     SNESLineSearchBTSetAlpha(linesearch, 0.0);
    440:   }
    441:   return(0);
    442: }

    445: /* -------------------------------------------------------------------------- */
    446: /*MC
    447:       SNESVINEWTONSSLS - Semi-smooth solver for variational inequalities based on Newton's method

    449:    Options Database:
    450: +   -snes_type <vinewtonssls,vinewtonrsls> a semi-smooth solver, a reduced space active set method
    451: -   -snes_vi_monitor - prints the number of active constraints at each iteration.

    453:    Level: beginner

    455:    References:
    456: +  1. -  T. S. Munson, F. Facchinei, M. C. Ferris, A. Fischer, and C. Kanzow. The semismooth
    457:      algorithm for large scale complementarity problems. INFORMS Journal on Computing, 13 (2001).
    458: -  2. -  T. S. Munson, and S. Benson. Flexible Complementarity Solvers for Large Scale
    459:      Applications, Optimization Methods and Software, 21 (2006).

    461: .seealso:  SNESVISetVariableBounds(), SNESVISetComputeVariableBounds(), SNESCreate(), SNES, SNESSetType(), SNESVINEWTONRSLS, SNESNEWTONTR, SNESLineSearchSetType(),SNESLineSearchSetPostCheck(), SNESLineSearchSetPreCheck()

    463: M*/
    464: PETSC_EXTERN PetscErrorCode SNESCreate_VINEWTONSSLS(SNES snes)
    465: {
    466:   PetscErrorCode    ierr;
    467:   SNES_VINEWTONSSLS *vi;

    470:   snes->ops->reset          = SNESReset_VINEWTONSSLS;
    471:   snes->ops->setup          = SNESSetUp_VINEWTONSSLS;
    472:   snes->ops->solve          = SNESSolve_VINEWTONSSLS;
    473:   snes->ops->destroy        = SNESDestroy_VI;
    474:   snes->ops->setfromoptions = SNESSetFromOptions_VINEWTONSSLS;
    475:   snes->ops->view           = NULL;

    477:   snes->usesksp = PETSC_TRUE;
    478:   snes->usesnpc = PETSC_FALSE;

    480:   snes->alwayscomputesfinalresidual = PETSC_FALSE;

    482:   PetscNewLog(snes,&vi);
    483:   snes->data = (void*)vi;

    485:   PetscObjectComposeFunction((PetscObject)snes,"SNESVISetVariableBounds_C",SNESVISetVariableBounds_VI);
    486:   PetscObjectComposeFunction((PetscObject)snes,"SNESVISetComputeVariableBounds_C",SNESVISetComputeVariableBounds_VI);
    487:   return(0);
    488: }