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ConstrainedOptPack: C++ Tools for Constrained (and Unconstrained) Optimization
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00001 // @HEADER 00002 // *********************************************************************** 00003 // 00004 // Moocho: Multi-functional Object-Oriented arCHitecture for Optimization 00005 // Copyright (2003) Sandia Corporation 00006 // 00007 // Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive 00008 // license for use of this work by or on behalf of the U.S. Government. 00009 // 00010 // Redistribution and use in source and binary forms, with or without 00011 // modification, are permitted provided that the following conditions are 00012 // met: 00013 // 00014 // 1. Redistributions of source code must retain the above copyright 00015 // notice, this list of conditions and the following disclaimer. 00016 // 00017 // 2. Redistributions in binary form must reproduce the above copyright 00018 // notice, this list of conditions and the following disclaimer in the 00019 // documentation and/or other materials provided with the distribution. 00020 // 00021 // 3. Neither the name of the Corporation nor the names of the 00022 // contributors may be used to endorse or promote products derived from 00023 // this software without specific prior written permission. 00024 // 00025 // THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY 00026 // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 00027 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 00028 // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE 00029 // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 00030 // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 00031 // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00032 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00033 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00034 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00035 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00036 // 00037 // Questions? Contact Roscoe A. Bartlett (rabartl@sandia.gov) 00038 // 00039 // *********************************************************************** 00040 // @HEADER 00041 00042 #include <ostream> 00043 #include <iomanip> 00044 #include <sstream> 00045 00046 #include "ConstrainedOptPack_DirectLineSearchArmQuad_Strategy.hpp" 00047 #include "ConstrainedOptPack_MeritFuncCalc1D.hpp" 00048 #include "check_nan_inf.h" 00049 00050 namespace ConstrainedOptPack { 00051 inline value_type min(value_type v1, value_type v2) { 00052 return (v1 < v2) ? v1 : v2; 00053 } 00054 inline value_type max(value_type v1, value_type v2) { 00055 return (v1 > v2) ? v1 : v2; 00056 } 00057 } 00058 00059 ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::DirectLineSearchArmQuad_Strategy( 00060 int max_iter 00061 ,value_type eta 00062 ,value_type min_frac 00063 ,value_type max_frac 00064 ,bool max_out_iter 00065 ) 00066 :max_iter_(max_iter) 00067 ,eta_(eta) 00068 ,min_frac_(min_frac) 00069 ,max_frac_(max_frac) 00070 ,max_out_iter_(max_out_iter) 00071 {} 00072 00073 void ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::set_max_iter(int max_iter) 00074 { 00075 max_iter_ = max_iter; 00076 } 00077 00078 int ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::max_iter() const 00079 { 00080 return max_iter_; 00081 } 00082 00083 int ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::num_iterations() const 00084 { 00085 return num_iter_; 00086 } 00087 00088 bool ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::do_line_search( 00089 const MeritFuncCalc1D& phi, value_type phi_k 00090 , value_type* alpha_k, value_type* phi_kp1 00091 , std::ostream* out ) 00092 { 00093 using std::setw; 00094 using std::endl; 00095 00096 if(*alpha_k < 0.0) { 00097 throw std::logic_error( "DirectLineSearchArmQuad_Strategy::do_line_search(): " 00098 "alpha_k can't start out less than 0.0" ); 00099 } 00100 00101 validate_parameters(); 00102 00103 int w = 20; 00104 int prec = 8; 00105 int prec_saved; 00106 if(out) { 00107 prec_saved = out->precision(); 00108 *out << std::setprecision(prec) 00109 << "\nStarting Armijo Quadratic interpolation linesearch ...\n"; 00110 } 00111 00112 // Loop initialization (technically the first iteration) 00113 00114 const value_type Dphi_k = phi.deriv(); 00115 00116 // output header 00117 if(out) { 00118 if(max_out_iter()) 00119 *out << "\nmax_out_iter == true, maxing out the number of iterations!"; 00120 *out << "\nDphi_k = " << Dphi_k 00121 << "\nphi_k = " << phi_k << "\n\n" 00122 << setw(5) << "itr" 00123 << setw(w) << "alpha_k" 00124 << setw(w) << "phi_kp1" 00125 << setw(w) << "phi_kp1-frac_phi\n" 00126 << setw(5) << "----" 00127 << setw(w) << "----------------" 00128 << setw(w) << "----------------" 00129 << setw(w) << "----------------\n"; 00130 } 00131 00132 // Check that this is a decent direction 00133 if(Dphi_k >= 0) throw DirectLineSearch_Strategy::NotDescentDirection( 00134 "DirectLineSearchArmQuad_Strategy::do_line_search(): " 00135 "The given d_k is not a descent direction for the given " 00136 "phi (phi.deriv() is >= 0)" ); 00137 00138 // keep memory of the best value 00139 value_type best_alpha = *alpha_k, best_phi = *phi_kp1; 00140 00141 // Perform linesearch. 00142 bool success = false; 00143 for( num_iter_ = 0; num_iter_ < max_iter(); ++num_iter_ ) { 00144 00145 // Print out this iteration. 00146 00147 value_type frac_phi = phi_k + eta() * (*alpha_k) * Dphi_k; 00148 if(out) 00149 *out << setw(5) << num_iter_ 00150 << setw(w) << *alpha_k 00151 << setw(w) << *phi_kp1 00152 << setw(w) << ((*phi_kp1)-frac_phi) << endl; 00153 00154 // Check that this is a valid number. 00155 if( RTOp_is_nan_inf( *phi_kp1 ) ) { 00156 // Cut back the step to min_frac * alpha_k 00157 *alpha_k = min_frac()*(*alpha_k); 00158 best_alpha = 0.0; 00159 best_phi = phi_k; 00160 } 00161 else { 00162 00163 // Armijo condition 00164 if( *phi_kp1 < frac_phi ) { 00165 // We have found an acceptable point 00166 success = true; 00167 if( !max_out_iter() || ( max_out_iter() && num_iter_ == max_iter() - 1 ) ) 00168 break; // get out of the loop 00169 } 00170 00171 // Select a new alpha to try: 00172 // alpha_k = ( min_frac*alpha_k <= quadratic interpolation <= max_frac*alpha_k ) 00173 00174 // Quadratic interpolation of alpha_k that minimizes phi. 00175 // We know the values of phi at the initail point and alpha_k and 00176 // the derivate of phi w.r.t alpha at the initial point and 00177 // that's enough information for a quandratic interpolation. 00178 00179 value_type alpha_quad = ( -0.5 * Dphi_k * (*alpha_k) * (*alpha_k) ) 00180 / ( (*phi_kp1) - phi_k - (*alpha_k) * Dphi_k ); 00181 00182 *alpha_k = min( max(min_frac()*(*alpha_k),alpha_quad), max_frac()*(*alpha_k) ); 00183 00184 } 00185 00186 // Evaluate the point 00187 00188 *phi_kp1 = phi(*alpha_k); 00189 00190 // Save the best point found 00191 if(*phi_kp1 < best_phi) { 00192 best_phi = *phi_kp1; 00193 best_alpha = *alpha_k; 00194 } 00195 00196 } 00197 00198 // Be nice and reset the precision 00199 if(out) { 00200 out->precision(prec_saved); 00201 } 00202 00203 if( success ) { 00204 return true; 00205 } 00206 00207 // Line search failure. Return the best point found and let the 00208 // client decide what to do. 00209 *alpha_k = best_alpha; 00210 *phi_kp1 = phi(best_alpha); // Make this the last call to phi(x) 00211 return false; 00212 } 00213 00214 void ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::print_algorithm( 00215 std::ostream& out, const std::string& L) const 00216 { 00217 out 00218 << L << "*** start line search using the Armijo cord test and quadratic interpolation of alpha\n" 00219 << L << "default: max_ls_iter = " << max_iter() << std::endl 00220 << L << " eta = " << eta() << std::endl 00221 << L << " min_frac = " << min_frac() << std::endl 00222 << L << " max_frac = " << max_frac() << std::endl 00223 << L << " max_out_iter = " << max_out_iter() << std::endl 00224 << L << "Dphi_k = phi.deriv()\n" 00225 << L << "if Dphi_k >= 0\n" 00226 << L << " throw not_descent_direction\n" 00227 << L << " end line search\n" 00228 << L << "end\n" 00229 << L << "best_alpha = alpha_k\n" 00230 << L << "best_phi = phi_kp1\n" 00231 << L << "for num_iter = 0... max_ls_iter\n" 00232 << L << " frac_phi = phi_k + eta * alpha_k * Dphi_k\n" 00233 << L << " print iteration\n" 00234 << L << " if phi_kp1 is not a valid number then\n" 00235 << L << " *** Cut back the step so the NLP's functions\n" 00236 << L << " *** will hopefully be defined.\n" 00237 << L << " alpha_k = min_frac * alpha_k\n" 00238 << L << " best_alpha = 0\n" 00239 << L << " best_phi = phi_k\n" 00240 << L << " else\n" 00241 << L << " if ( phi_kp1 < frac_phi ) then\n" 00242 << L << " *** We have found an acceptable point\n" 00243 << L << " if( !max_out_iter || max_out_iter && num_iter == max_ls_iter - 1 ) )\n" 00244 << L << " end line search\n" 00245 << L << " end\n" 00246 << L << " end\n" 00247 << L << " *** Use a quadratic interpoation to minimize phi(alpha)\n" 00248 << L << " alpha_quad = (-0.5 * Dphi_k * alpha_k^2) / ( phi_kp1 - phi_k - alpha_k*Dphi_k )\n" 00249 << L << " alpha_k = min( max( min_frac*alpha_k, alpha_quad ), max_frac*alpha_k )\n" 00250 << L << " end\n" 00251 << L << " phi_kp1 = phi(alpha_k)\n" 00252 << L << " if phi_kp1 < best_phi\n" 00253 << L << " best_phi = phi_kp1\n" 00254 << L << " best_alpha = alpha_k\n" 00255 << L << " end\n" 00256 << L << "end\n" 00257 << L << "*** If you get there the line search failed.\n" 00258 << L << "alpha_k = best_alpha\n" 00259 << L << "phi_kp1 = phi(alpha_k)\n" 00260 << L << "linesearch_failure = true\n"; 00261 } 00262 00263 void ConstrainedOptPack::DirectLineSearchArmQuad_Strategy::validate_parameters() const 00264 { 00265 if( eta() < 0.0 || 1.0 < eta() ) { 00266 std::ostringstream omsg; 00267 omsg 00268 << "DirectLineSearchArmQuad_Strategy::validate_parameters() : " 00269 << "Error, eta = " << eta() << " is not in the range [0, 1]"; 00270 throw std::invalid_argument( omsg.str() ); 00271 } 00272 if( min_frac() < 0.0 || 1.0 < min_frac() ) { 00273 std::ostringstream omsg; 00274 omsg 00275 << "DirectLineSearchArmQuad_Strategy::validate_parameters() : " 00276 << "Error, min_frac = " << min_frac() << " is not in the range [0, 1]"; 00277 throw std::invalid_argument( omsg.str() ); 00278 } 00279 if( max_frac() < 0.0 || ( !max_out_iter() && 1.0 < max_frac() ) ) { 00280 std::ostringstream omsg; 00281 omsg 00282 << "DirectLineSearchArmQuad_Strategy::validate_parameters() : " 00283 << "Error, max_frac = " << max_frac() << " is not in the range [0, 1]"; 00284 throw std::invalid_argument( omsg.str() ); 00285 } 00286 if( max_frac() < min_frac() ) { 00287 std::ostringstream omsg; 00288 omsg 00289 << "DirectLineSearchArmQuad_Strategy::validate_parameters() : " 00290 << "Error, max_frac = " << max_frac() 00291 << " < min_frac = " << min_frac();; 00292 throw std::invalid_argument( omsg.str() ); 00293 } 00294 }
1.7.6.1