gtsam/gtsam_unstable/linear/LPInitSolver.cpp

111 lines
3.9 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file LPInitSolver.h
* @brief This finds a feasible solution for an LP problem
* @author Duy Nguyen Ta
* @author Ivan Dario Jimenez
* @date 6/16/16
*/
#include <gtsam_unstable/linear/LPInitSolver.h>
#include <gtsam_unstable/linear/LPSolver.h>
#include <gtsam_unstable/linear/InfeasibleOrUnboundedProblem.h>
namespace gtsam {
/******************************************************************************/
VectorValues LPInitSolver::solve() const {
// Build the graph to solve for the initial value of the initial problem
GaussianFactorGraph::shared_ptr initOfInitGraph = buildInitOfInitGraph();
VectorValues x0 = initOfInitGraph->optimize();
double y0 = compute_y0(x0);
Key yKey = maxKey(lp_) + 1; // the unique key for y0
VectorValues xy0(x0);
xy0.insert(yKey, Vector::Constant(1, y0));
// Formulate and solve the initial LP
LP::shared_ptr initLP = buildInitialLP(yKey);
// solve the initialLP
LPSolver lpSolveInit(*initLP);
VectorValues xyInit = lpSolveInit.optimize(xy0).first;
double yOpt = xyInit.at(yKey)[0];
xyInit.erase(yKey);
if (yOpt > 0)
throw InfeasibleOrUnboundedProblem();
else
return xyInit;
}
/******************************************************************************/
LP::shared_ptr LPInitSolver::buildInitialLP(Key yKey) const {
LP::shared_ptr initLP(new LP());
initLP->cost = LinearCost(yKey, I_1x1); // min y
initLP->equalities = lp_.equalities; // st. Ax = b
initLP->inequalities =
addSlackVariableToInequalities(yKey,
lp_.inequalities); // Cx-y <= d
return initLP;
}
/******************************************************************************/
GaussianFactorGraph::shared_ptr LPInitSolver::buildInitOfInitGraph() const {
// first add equality constraints Ax = b
GaussianFactorGraph::shared_ptr initGraph(
new GaussianFactorGraph(lp_.equalities));
// create factor ||x||^2 and add to the graph
const KeyDimMap& constrainedKeyDim = lp_.constrainedKeyDimMap();
for (const auto& [key, _] : constrainedKeyDim) {
size_t dim = constrainedKeyDim.at(key);
initGraph->push_back(
JacobianFactor(key, Matrix::Identity(dim, dim), Vector::Zero(dim)));
}
return initGraph;
}
/******************************************************************************/
double LPInitSolver::compute_y0(const VectorValues& x0) const {
double y0 = -std::numeric_limits<double>::infinity();
for (const auto& factor : lp_.inequalities) {
double error = factor->error(x0);
if (error > y0) y0 = error;
}
return y0;
}
/******************************************************************************/
std::vector<std::pair<Key, Matrix> > LPInitSolver::collectTerms(
const LinearInequality& factor) const {
std::vector<std::pair<Key, Matrix> > terms;
for (Factor::const_iterator it = factor.begin(); it != factor.end(); it++) {
terms.push_back(make_pair(*it, factor.getA(it)));
}
return terms;
}
/******************************************************************************/
InequalityFactorGraph LPInitSolver::addSlackVariableToInequalities(
Key yKey, const InequalityFactorGraph& inequalities) const {
InequalityFactorGraph slackInequalities;
for (const auto& factor : lp_.inequalities) {
std::vector<std::pair<Key, Matrix> > terms = collectTerms(*factor); // Cx
terms.push_back(make_pair(yKey, Matrix::Constant(1, 1, -1.0))); // -y
double d = factor->getb()[0];
slackInequalities.push_back(LinearInequality(terms, d, factor->dualKey()));
}
return slackInequalities;
}
}