Actual source code: nls.h

petsc-3.6.1 2015-08-06
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  1: /*
  2: Context for a Newton line search method (unconstrained minimization)
  3: */

  5: #ifndef __TAO_NLS_H
  7: #include <petsc/private/taoimpl.h>

  9: typedef struct {
 10:   Mat M;

 12:   Vec D;
 13:   Vec W;

 15:   Vec Xold;
 16:   Vec Gold;
 17:   Vec Diag;

 19:   /*  Parameters when updating the perturbation added to the Hessian matrix */
 20:   PetscReal sval;          /*  Starting perturbation value, default zero */

 22:   PetscReal imin;          /*  Minimum perturbation added during initialization  */
 23:   PetscReal imax;          /*  Maximum perturbation added during initialization */
 24:   PetscReal imfac;         /*  Merit function factor during initialization */

 26:   PetscReal pmin;          /*  Minimim perturbation value */
 27:   PetscReal pmax;          /*  Maximum perturbation value */
 28:   PetscReal pgfac;         /*  Perturbation growth factor */
 29:   PetscReal psfac;         /*  Perturbation shrink factor */
 30:   PetscReal pmgfac;        /*  Merit function growth factor */
 31:   PetscReal pmsfac;        /*  Merit function shrink factor */

 33:   /* The perturbation to the Hessian matrix is initialized and updated
 34:      according to the following scheme:

 36:        pert = sval;

 38:        do until convergence
 39:          shift Hessian by pert
 40:          solve Newton system

 42:          if (linear solver failed or did not compute a descent direction)
 43:            use steepest descent direction and increase perturbation

 45:            if (0 == pert)
 46:              initialize perturbation
 47:              pert = min(imax, max(imin, imfac * norm(G)))
 48:            else
 49:              increase perturbation
 50:              pert = min(pmax, max(pgfac * pert, pmgfac * norm(G)))
 51:            fi
 52:          else
 53:            use linear solver direction and decrease perturbation

 55:            pert = min(psfac * pert, pmsfac * norm(G))
 56:            if (pert < pmin)
 57:              pert = 0
 58:            fi
 59:          fi

 61:          perform line search
 62:          function and gradient evaluation
 63:          check convergence
 64:        od
 65:   */

 67:   /*  Parameters when updating the trust-region radius based on steplength */
 68:   PetscReal nu1;                /*  used to compute trust-region radius */
 69:   PetscReal nu2;                /*  used to compute trust-region radius */
 70:   PetscReal nu3;                /*  used to compute trust-region radius */
 71:   PetscReal nu4;                /*  used to compute trust-region radius */

 73:   PetscReal omega1;        /*  factor used for trust-region update */
 74:   PetscReal omega2;        /*  factor used for trust-region update */
 75:   PetscReal omega3;        /*  factor used for trust-region update */
 76:   PetscReal omega4;        /*  factor used for trust-region update */
 77:   PetscReal omega5;        /*  factor used for trust-region update */

 79:   /* if   step < nu1            (very bad step)
 80:        radius = omega1 * min(norm(d), radius)
 81:      elif step < nu2            (bad step)
 82:        radius = omega2 * min(norm(d), radius)
 83:      elif step < nu3            (okay step)
 84:        radius = omega3 * radius;
 85:      elif step < nu4            (good step)
 86:        radius = max(omega4 * norm(d), radius)
 87:      else                       (very good step)
 88:        radius = max(omega5 * norm(d), radius)
 89:      fi
 90:   */

 92:   /*  Parameters when updating the trust-region radius based on reduction */
 93:   PetscReal eta1;               /*  used to compute trust-region radius */
 94:   PetscReal eta2;               /*  used to compute trust-region radius */
 95:   PetscReal eta3;               /*  used to compute trust-region radius */
 96:   PetscReal eta4;               /*  used to compute trust-region radius */

 98:   PetscReal alpha1;        /*  factor used for trust-region update */
 99:   PetscReal alpha2;        /*  factor used for trust-region update */
100:   PetscReal alpha3;        /*  factor used for trust-region update */
101:   PetscReal alpha4;        /*  factor used for trust-region update */
102:   PetscReal alpha5;        /*  factor used for trust-region update */

104:   /* kappa = ared / pred
105:      if   kappa < eta1          (very bad step)
106:        radius = alpha1 * min(norm(d), radius)
107:      elif kappa < eta2          (bad step)
108:        radius = alpha2 * min(norm(d), radius)
109:      elif kappa < eta3          (okay step)
110:        radius = alpha3 * radius;
111:      elif kappa < eta4          (good step)
112:        radius = max(alpha4 * norm(d), radius)
113:      else                       (very good step)
114:        radius = max(alpha5 * norm(d), radius)
115:      fi
116:   */

118:   /*  Parameters when updating the trust-region radius based on interpolation */
119:   PetscReal mu1;                /*  used for model agreement in interpolation */
120:   PetscReal mu2;                /*  used for model agreement in interpolation */

122:   PetscReal gamma1;     /*  factor used for interpolation */
123:   PetscReal gamma2;     /*  factor used for interpolation */
124:   PetscReal gamma3;     /*  factor used for interpolation */
125:   PetscReal gamma4;     /*  factor used for interpolation */

127:   PetscReal theta;              /*  factor used for interpolation */

129:   /* kappa = ared / pred
130:      if   kappa >= 1.0 - mu1    (very good step)
131:        choose tau in [gamma3, gamma4]
132:        radius = max(tau * norm(d), radius)
133:      elif kappa >= 1.0 - mu2    (good step)
134:        choose tau in [gamma2, gamma3]
135:        if (tau >= 1.0)
136:          radius = max(tau * norm(d), radius)
137:        else
138:          radius = tau * min(norm(d), radius)
139:        fi
140:      else                       (bad step)
141:        choose tau in [gamma1, 1.0]
142:        radius = tau * min(norm(d), radius)
143:      fi
144:   */

146:   /*  Parameters when initializing trust-region radius based on interpolation */
147:   PetscReal mu1_i;              /*  used for model agreement in interpolation */
148:   PetscReal mu2_i;              /*  used for model agreement in interpolation */

150:   PetscReal gamma1_i;   /*  factor used for interpolation */
151:   PetscReal gamma2_i;   /*  factor used for interpolation */
152:   PetscReal gamma3_i;   /*  factor used for interpolation */
153:   PetscReal gamma4_i;   /*  factor used for interpolation */

155:   PetscReal theta_i;    /*  factor used for interpolation */

157:   /*  Other parameters */
158:   PetscReal min_radius;    /*  lower bound on initial radius value */
159:   PetscReal max_radius;    /*  upper bound on trust region radius */
160:   PetscReal epsilon;       /*  tolerance used when computing ared/pred */

162:   PetscInt newt;                /*  Newton directions attempted */
163:   PetscInt bfgs;                /*  BFGS directions attempted */
164:   PetscInt sgrad;               /*  Scaled gradient directions attempted */
165:   PetscInt grad;                /*  Gradient directions attempted */


168:   PetscInt ksp_type;            /*  KSP method for the code */
169:   PetscInt pc_type;             /*  Preconditioner for the code */
170:   PetscInt bfgs_scale_type;     /*  Scaling matrix to used for the bfgs preconditioner */
171:   PetscInt init_type;   /*  Trust-region initialization method */
172:   PetscInt update_type;      /*  Trust-region update method */

174:   PetscInt ksp_atol;
175:   PetscInt ksp_rtol;
176:   PetscInt ksp_ctol;
177:   PetscInt ksp_negc;
178:   PetscInt ksp_dtol;
179:   PetscInt ksp_iter;
180:   PetscInt ksp_othr;
181: } TAO_NLS;

183: #endif /* ifndef __TAO_NLS_H */