Date: 2022-03-31T04:48:30+00:00

Actual source code: viss.c

      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: {
     20:   VecNormBegin(phi,NORM_2,phinorm);
     21:   VecNormEnd(phi,NORM_2,phinorm);

     23:   *merit = 0.5*(*phinorm)*(*phinorm);
     24:   return 0;
     25: }

     27: static inline PetscScalar Phi(PetscScalar a,PetscScalar b)
     28: {
     29:   return a + b - PetscSqrtScalar(a*a + b*b);
     30: }

     32: static inline PetscScalar DPhi(PetscScalar a,PetscScalar b)
     33: {
     34:   if ((PetscAbsScalar(a) >= 1.e-6) || (PetscAbsScalar(b) >= 1.e-6)) return 1.0 - a/ PetscSqrtScalar(a*a + b*b);
     35:   else return .5;
     36: }

     38: /*
     39:    SNESVIComputeFunction - Reformulates a system of nonlinear equations in mixed complementarity form to a system of nonlinear equations in semismooth form.

     41:    Input Parameters:
     42: .  snes - the SNES context
     43: .  X - current iterate
     44: .  functx - user defined function context

     46:    Output Parameters:
     47: .  phi - Semismooth function

     49: */
     50: static PetscErrorCode SNESVIComputeFunction(SNES snes,Vec X,Vec phi,void *functx)
     51: {
     52:   SNES_VINEWTONSSLS *vi = (SNES_VINEWTONSSLS*)snes->data;
     53:   Vec               Xl  = snes->xl,Xu = snes->xu,F = snes->vec_func;
     54:   PetscScalar       *phi_arr,*f_arr,*l,*u;
     55:   const PetscScalar *x_arr;
     56:   PetscInt          i,nlocal;

     58:   (*vi->computeuserfunction)(snes,X,F,functx);
     59:   VecGetLocalSize(X,&nlocal);
     60:   VecGetArrayRead(X,&x_arr);
     61:   VecGetArray(F,&f_arr);
     62:   VecGetArray(Xl,&l);
     63:   VecGetArray(Xu,&u);
     64:   VecGetArray(phi,&phi_arr);

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

     80:   VecRestoreArrayRead(X,&x_arr);
     81:   VecRestoreArray(F,&f_arr);
     82:   VecRestoreArray(Xl,&l);
     83:   VecRestoreArray(Xu,&u);
     84:   VecRestoreArray(phi,&phi_arr);
     85:   return 0;
     86: }

     88: /*
     89:    SNESVIComputeBsubdifferentialVectors - Computes the diagonal shift (Da) and row scaling (Db) vectors needed for the
     90:                                           the semismooth jacobian.
     91: */
     92: PetscErrorCode SNESVIComputeBsubdifferentialVectors(SNES snes,Vec X,Vec F,Mat jac,Vec Da,Vec Db)
     93: {
     94:   PetscScalar    *l,*u,*x,*f,*da,*db,da1,da2,db1,db2;
     95:   PetscInt       i,nlocal;

     97:   VecGetArray(X,&x);
     98:   VecGetArray(F,&f);
     99:   VecGetArray(snes->xl,&l);
    100:   VecGetArray(snes->xu,&u);
    101:   VecGetArray(Da,&da);
    102:   VecGetArray(Db,&db);
    103:   VecGetLocalSize(X,&nlocal);

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

    128:   VecRestoreArray(X,&x);
    129:   VecRestoreArray(F,&f);
    130:   VecRestoreArray(snes->xl,&l);
    131:   VecRestoreArray(snes->xu,&u);
    132:   VecRestoreArray(Da,&da);
    133:   VecRestoreArray(Db,&db);
    134:   return 0;
    135: }

    137: /*
    138:    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.

    140:    Input Parameters:
    141: .  Da       - Diagonal shift vector for the semismooth jacobian.
    142: .  Db       - Row scaling vector for the semismooth jacobian.

    144:    Output Parameters:
    145: .  jac      - semismooth jacobian
    146: .  jac_pre  - optional preconditioning matrix

    148:    Notes:
    149:    The semismooth jacobian matrix is given by
    150:    jac = Da + Db*jacfun
    151:    where Db is the row scaling matrix stored as a vector,
    152:          Da is the diagonal perturbation matrix stored as a vector
    153:    and   jacfun is the jacobian of the original nonlinear function.
    154: */
    155: PetscErrorCode SNESVIComputeJacobian(Mat jac, Mat jac_pre,Vec Da, Vec Db)
    156: {

    158:   /* Do row scaling  and add diagonal perturbation */
    159:   MatDiagonalScale(jac,Db,NULL);
    160:   MatDiagonalSet(jac,Da,ADD_VALUES);
    161:   if (jac != jac_pre) { /* If jac and jac_pre are different */
    162:     MatDiagonalScale(jac_pre,Db,NULL);
    163:     MatDiagonalSet(jac_pre,Da,ADD_VALUES);
    164:   }
    165:   return 0;
    166: }

    168: /*
    169:    SNESVIComputeMeritFunctionGradient - Computes the gradient of the merit function psi.

    171:    Input Parameters:
    172:    phi - semismooth function.
    173:    H   - semismooth jacobian

    175:    Output Parameters:
    176:    dpsi - merit function gradient

    178:    Notes:
    179:   The merit function gradient is computed as follows
    180:         dpsi = H^T*phi
    181: */
    182: PetscErrorCode SNESVIComputeMeritFunctionGradient(Mat H, Vec phi, Vec dpsi)
    183: {
    184:   MatMultTranspose(H,phi,dpsi);
    185:   return 0;
    186: }

    188: /*
    189:    SNESSolve_VINEWTONSSLS - Solves the complementarity problem with a semismooth Newton
    190:    method using a line search.

    192:    Input Parameters:
    193: .  snes - the SNES context

    195:    Application Interface Routine: SNESSolve()

    197:    Notes:
    198:    This implements essentially a semismooth Newton method with a
    199:    line search. The default line search does not do any line search
    200:    but rather takes a full Newton step.

    202:    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

    204: */
    205: PetscErrorCode SNESSolve_VINEWTONSSLS(SNES snes)
    206: {
    207:   SNES_VINEWTONSSLS    *vi = (SNES_VINEWTONSSLS*)snes->data;
    208:   PetscInt             maxits,i,lits;
    209:   SNESLineSearchReason lssucceed;
    210:   PetscReal            gnorm,xnorm=0,ynorm;
    211:   Vec                  Y,X,F;
    212:   KSPConvergedReason   kspreason;
    213:   DM                   dm;
    214:   DMSNES               sdm;

    216:   SNESGetDM(snes,&dm);
    217:   DMGetDMSNES(dm,&sdm);

    219:   vi->computeuserfunction   = sdm->ops->computefunction;
    220:   sdm->ops->computefunction = SNESVIComputeFunction;

    222:   snes->numFailures            = 0;
    223:   snes->numLinearSolveFailures = 0;
    224:   snes->reason                 = SNES_CONVERGED_ITERATING;

    226:   maxits = snes->max_its;               /* maximum number of iterations */
    227:   X      = snes->vec_sol;               /* solution vector */
    228:   F      = snes->vec_func;              /* residual vector */
    229:   Y      = snes->work[0];               /* work vectors */

    231:   PetscObjectSAWsTakeAccess((PetscObject)snes);
    232:   snes->iter = 0;
    233:   snes->norm = 0.0;
    234:   PetscObjectSAWsGrantAccess((PetscObject)snes);

    236:   SNESVIProjectOntoBounds(snes,X);
    237:   SNESComputeFunction(snes,X,vi->phi);
    238:   if (snes->domainerror) {
    239:     snes->reason              = SNES_DIVERGED_FUNCTION_DOMAIN;
    240:     sdm->ops->computefunction = vi->computeuserfunction;
    241:     return 0;
    242:   }
    243:   /* Compute Merit function */
    244:   SNESVIComputeMeritFunction(vi->phi,&vi->merit,&vi->phinorm);

    246:   VecNormBegin(X,NORM_2,&xnorm);        /* xnorm <- ||x||  */
    247:   VecNormEnd(X,NORM_2,&xnorm);
    248:   SNESCheckFunctionNorm(snes,vi->merit);

    250:   PetscObjectSAWsTakeAccess((PetscObject)snes);
    251:   snes->norm = vi->phinorm;
    252:   PetscObjectSAWsGrantAccess((PetscObject)snes);
    253:   SNESLogConvergenceHistory(snes,vi->phinorm,0);
    254:   SNESMonitor(snes,0,vi->phinorm);

    256:   /* test convergence */
    257:   (*snes->ops->converged)(snes,0,0.0,0.0,vi->phinorm,&snes->reason,snes->cnvP);
    258:   if (snes->reason) {
    259:     sdm->ops->computefunction = vi->computeuserfunction;
    260:     return 0;
    261:   }

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

    265:     /* Call general purpose update function */
    266:     if (snes->ops->update) {
    267:       (*snes->ops->update)(snes, snes->iter);
    268:     }

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

    272:     /* Get the jacobian -- note that the function must be the original function for snes_fd and snes_fd_color to work for this*/
    273:     sdm->ops->computefunction = vi->computeuserfunction;
    274:     SNESComputeJacobian(snes,X,snes->jacobian,snes->jacobian_pre);
    275:     SNESCheckJacobianDomainerror(snes);
    276:     sdm->ops->computefunction = SNESVIComputeFunction;

    278:     /* Get the diagonal shift and row scaling vectors */
    279:     SNESVIComputeBsubdifferentialVectors(snes,X,F,snes->jacobian,vi->Da,vi->Db);
    280:     /* Compute the semismooth jacobian */
    281:     SNESVIComputeJacobian(snes->jacobian,snes->jacobian_pre,vi->Da,vi->Db);
    282:     /* Compute the merit function gradient */
    283:     SNESVIComputeMeritFunctionGradient(snes->jacobian,vi->phi,vi->dpsi);
    284:     KSPSetOperators(snes->ksp,snes->jacobian,snes->jacobian_pre);
    285:     KSPSolve(snes->ksp,vi->phi,Y);
    286:     KSPGetConvergedReason(snes->ksp,&kspreason);

    288:     if (kspreason < 0) {
    289:       if (++snes->numLinearSolveFailures >= snes->maxLinearSolveFailures) {
    290:         PetscInfo(snes,"iter=%D, number linear solve failures %D greater than current SNES allowed, stopping solve\n",snes->iter,snes->numLinearSolveFailures);
    291:         snes->reason = SNES_DIVERGED_LINEAR_SOLVE;
    292:         break;
    293:       }
    294:     }
    295:     KSPGetIterationNumber(snes->ksp,&lits);
    296:     snes->linear_its += lits;
    297:     PetscInfo(snes,"iter=%D, linear solve iterations=%D\n",snes->iter,lits);
    298:     /*
    299:     if (snes->ops->precheck) {
    300:       PetscBool changed_y = PETSC_FALSE;
    301:       (*snes->ops->precheck)(snes,X,Y,snes->precheck,&changed_y);
    302:     }

    304:     if (PetscLogPrintInfo) {
    305:       SNESVICheckResidual_Private(snes,snes->jacobian,F,Y,G,W);
    306:     }
    307:     */
    308:     /* Compute a (scaled) negative update in the line search routine:
    309:          Y <- X - lambda*Y
    310:        and evaluate G = function(Y) (depends on the line search).
    311:     */
    312:     VecCopy(Y,snes->vec_sol_update);
    313:     ynorm = 1; gnorm = vi->phinorm;
    314:     SNESLineSearchApply(snes->linesearch, X, vi->phi, &gnorm, Y);
    315:     SNESLineSearchGetReason(snes->linesearch, &lssucceed);
    316:     SNESLineSearchGetNorms(snes->linesearch, &xnorm, &gnorm, &ynorm);
    317:     PetscInfo(snes,"fnorm=%18.16e, gnorm=%18.16e, ynorm=%18.16e, lssucceed=%d\n",(double)vi->phinorm,(double)gnorm,(double)ynorm,(int)lssucceed);
    318:     if (snes->reason == SNES_DIVERGED_FUNCTION_COUNT) break;
    319:     if (snes->domainerror) {
    320:       snes->reason              = SNES_DIVERGED_FUNCTION_DOMAIN;
    321:       sdm->ops->computefunction = vi->computeuserfunction;
    322:       return 0;
    323:     }
    324:     if (lssucceed) {
    325:       if (++snes->numFailures >= snes->maxFailures) {
    326:         PetscBool ismin;
    327:         snes->reason = SNES_DIVERGED_LINE_SEARCH;
    328:         SNESVICheckLocalMin_Private(snes,snes->jacobian,vi->phi,X,gnorm,&ismin);
    329:         if (ismin) snes->reason = SNES_DIVERGED_LOCAL_MIN;
    330:         break;
    331:       }
    332:     }
    333:     /* Update function and solution vectors */
    334:     vi->phinorm = gnorm;
    335:     vi->merit   = 0.5*vi->phinorm*vi->phinorm;
    336:     /* Monitor convergence */
    337:     PetscObjectSAWsTakeAccess((PetscObject)snes);
    338:     snes->iter = i+1;
    339:     snes->norm = vi->phinorm;
    340:     snes->xnorm = xnorm;
    341:     snes->ynorm = ynorm;
    342:     PetscObjectSAWsGrantAccess((PetscObject)snes);
    343:     SNESLogConvergenceHistory(snes,snes->norm,lits);
    344:     SNESMonitor(snes,snes->iter,snes->norm);
    345:     /* Test for convergence, xnorm = || X || */
    346:     if (snes->ops->converged != SNESConvergedSkip) VecNorm(X,NORM_2,&xnorm);
    347:     (*snes->ops->converged)(snes,snes->iter,xnorm,ynorm,vi->phinorm,&snes->reason,snes->cnvP);
    348:     if (snes->reason) break;
    349:   }
    350:   if (i == maxits) {
    351:     PetscInfo(snes,"Maximum number of iterations has been reached: %D\n",maxits);
    352:     if (!snes->reason) snes->reason = SNES_DIVERGED_MAX_IT;
    353:   }
    354:   sdm->ops->computefunction = vi->computeuserfunction;
    355:   return 0;
    356: }

    358: /* -------------------------------------------------------------------------- */
    359: /*
    360:    SNESSetUp_VINEWTONSSLS - Sets up the internal data structures for the later use
    361:    of the SNES nonlinear solver.

    363:    Input Parameter:
    364: .  snes - the SNES context

    366:    Application Interface Routine: SNESSetUp()

    368:    Notes:
    369:    For basic use of the SNES solvers, the user need not explicitly call
    370:    SNESSetUp(), since these actions will automatically occur during
    371:    the call to SNESSolve().
    372:  */
    373: PetscErrorCode SNESSetUp_VINEWTONSSLS(SNES snes)
    374: {
    375:   SNES_VINEWTONSSLS *vi = (SNES_VINEWTONSSLS*) snes->data;

    377:   SNESSetUp_VI(snes);
    378:   VecDuplicate(snes->vec_sol, &vi->dpsi);
    379:   VecDuplicate(snes->vec_sol, &vi->phi);
    380:   VecDuplicate(snes->vec_sol, &vi->Da);
    381:   VecDuplicate(snes->vec_sol, &vi->Db);
    382:   VecDuplicate(snes->vec_sol, &vi->z);
    383:   VecDuplicate(snes->vec_sol, &vi->t);
    384:   return 0;
    385: }
    386: /* -------------------------------------------------------------------------- */
    387: PetscErrorCode SNESReset_VINEWTONSSLS(SNES snes)
    388: {
    389:   SNES_VINEWTONSSLS *vi = (SNES_VINEWTONSSLS*) snes->data;

    391:   SNESReset_VI(snes);
    392:   VecDestroy(&vi->dpsi);
    393:   VecDestroy(&vi->phi);
    394:   VecDestroy(&vi->Da);
    395:   VecDestroy(&vi->Db);
    396:   VecDestroy(&vi->z);
    397:   VecDestroy(&vi->t);
    398:   return 0;
    399: }

    401: /* -------------------------------------------------------------------------- */
    402: /*
    403:    SNESSetFromOptions_VINEWTONSSLS - Sets various parameters for the SNESVI method.

    405:    Input Parameter:
    406: .  snes - the SNES context

    408:    Application Interface Routine: SNESSetFromOptions()
    409: */
    410: static PetscErrorCode SNESSetFromOptions_VINEWTONSSLS(PetscOptionItems *PetscOptionsObject,SNES snes)
    411: {
    412:   SNESSetFromOptions_VI(PetscOptionsObject,snes);
    413:   PetscOptionsHead(PetscOptionsObject,"SNES semismooth method options");
    414:   PetscOptionsTail();
    415:   return 0;
    416: }

    418: /* -------------------------------------------------------------------------- */
    419: /*MC
    420:       SNESVINEWTONSSLS - Semi-smooth solver for variational inequalities based on Newton's method

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

    426:    Level: beginner

    428:    References:
    429: +  * -  T. S. Munson, F. Facchinei, M. C. Ferris, A. Fischer, and C. Kanzow. The semismooth
    430:      algorithm for large scale complementarity problems. INFORMS Journal on Computing, 13 (2001).
    431: -  * -  T. S. Munson, and S. Benson. Flexible Complementarity Solvers for Large Scale
    432:      Applications, Optimization Methods and Software, 21 (2006).

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

    436: M*/
    437: PETSC_EXTERN PetscErrorCode SNESCreate_VINEWTONSSLS(SNES snes)
    438: {
    439:   SNES_VINEWTONSSLS *vi;
    440:   SNESLineSearch    linesearch;

    442:   snes->ops->reset          = SNESReset_VINEWTONSSLS;
    443:   snes->ops->setup          = SNESSetUp_VINEWTONSSLS;
    444:   snes->ops->solve          = SNESSolve_VINEWTONSSLS;
    445:   snes->ops->destroy        = SNESDestroy_VI;
    446:   snes->ops->setfromoptions = SNESSetFromOptions_VINEWTONSSLS;
    447:   snes->ops->view           = NULL;

    449:   snes->usesksp = PETSC_TRUE;
    450:   snes->usesnpc = PETSC_FALSE;

    452:   SNESGetLineSearch(snes, &linesearch);
    453:   if (!((PetscObject)linesearch)->type_name) {
    454:     SNESLineSearchSetType(linesearch, SNESLINESEARCHBT);
    455:     SNESLineSearchBTSetAlpha(linesearch, 0.0);
    456:   }

    458:   snes->alwayscomputesfinalresidual = PETSC_FALSE;

    460:   PetscNewLog(snes,&vi);
    461:   snes->data = (void*)vi;

    463:   PetscObjectComposeFunction((PetscObject)snes,"SNESVISetVariableBounds_C",SNESVISetVariableBounds_VI);
    464:   PetscObjectComposeFunction((PetscObject)snes,"SNESVISetComputeVariableBounds_C",SNESVISetComputeVariableBounds_VI);
    465:   return 0;
    466: }