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NLPWBCounterExampleMain.cpp
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00004 // Moocho: Multi-functional Object-Oriented arCHitecture for Optimization
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00041 
00042 #include <iostream>
00043 
00044 #include "NLPInterfacePack_NLPWBCounterExample.hpp"
00045 #include "MoochoPack_MoochoSolver.hpp"
00046 #include "Teuchos_GlobalMPISession.hpp"
00047 #include "Teuchos_CommandLineProcessor.hpp"
00048 #include "Teuchos_StandardCatchMacros.hpp"
00049 
00050 int main( int argc, char* argv[] )
00051 {
00052   using MoochoPack::MoochoSolver;
00053   using NLPInterfacePack::NLPWBCounterExample;
00054   using Teuchos::CommandLineProcessor;
00055   bool success = true;
00056 
00057   Teuchos::GlobalMPISession mpiSession(&argc, &argv);
00058 
00059   try {
00060 
00061     MoochoSolver  solver;
00062   
00063     //
00064     // Get options from the command line
00065     //
00066     
00067     double   xinit[3]          = { 0.0, 0.0, 0.0 };
00068     double   a                 = 0.0;
00069     double   b                 = 1.0;
00070     bool     nlp_selects_basis = true;
00071     bool     linear_obj        = true;
00072 
00073     CommandLineProcessor  clp(false); // don't throw exceptions
00074     solver.setup_commandline_processor(&clp);
00075     clp.setOption( "x1-init",  &xinit[0], "Initail guess for x(1)" );
00076     clp.setOption( "x2-init",  &xinit[1], "Initail guess for x(2)" );
00077     clp.setOption( "x3-init",  &xinit[2], "Initail guess for x(3)" );
00078     clp.setOption( "a",  &a, "Constant for c(1)" );
00079     clp.setOption( "b",  &b, "Constant for c(2)" );
00080     clp.setOption(
00081       "nlp-selects-basis", "no-nlp-selects-basis", &nlp_selects_basis
00082       ,"Determine if NLP will select basis" );
00083     clp.setOption(
00084       "linear-obj", "nonlinear-obj", &linear_obj
00085       ,"Determine if objective is linear" );
00086     CommandLineProcessor::EParseCommandLineReturn
00087       parse_return = clp.parse(argc,argv,&std::cerr);
00088     if( parse_return != CommandLineProcessor::PARSE_SUCCESSFUL )
00089       return parse_return;
00090     
00091     //
00092     // Create the NLP and solve it
00093     //
00094 
00095     // Create the NLP
00096     NLPWBCounterExample
00097       nlp(xinit,a,b,nlp_selects_basis,linear_obj);
00098     // Set the NLP
00099     solver.set_nlp( Teuchos::rcp(&nlp,false) );
00100     // Solve the NLP
00101     const MoochoSolver::ESolutionStatus
00102       solution_status = solver.solve_nlp();
00103     
00104     //
00105     // Return the solution status (0 if sucessfull)
00106     //
00107 
00108     return solution_status;
00109 
00110   }
00111   TEUCHOS_STANDARD_CATCH_STATEMENTS(true,std::cout,success)
00112 
00113   return MoochoSolver::SOLVE_RETURN_EXCEPTION;
00114 
00115 }
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