ceres-solver / ceres-solver / a3dde68770de810e0962e30575e6a810dff22650 / . / internal / ceres / trust_region_step_evaluator.h

// Ceres Solver - A fast non-linear least squares minimizer | |

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// Author: sameeragarwal@google.com (Sameer Agarwal) | |

#ifndef CERES_INTERNAL_TRUST_REGION_STEP_EVALUATOR_H_ | |

#define CERES_INTERNAL_TRUST_REGION_STEP_EVALUATOR_H_ | |

namespace ceres { | |

namespace internal { | |

// The job of the TrustRegionStepEvaluator is to evaluate the quality | |

// of a step, i.e., how the cost of a step compares with the reduction | |

// in the objective of the trust region problem. | |

// | |

// Classic trust region methods are descent methods, in that they only | |

// accept a point if it strictly reduces the value of the objective | |

// function. They do this by measuring the quality of a step as | |

// | |

// cost_change / model_cost_change. | |

// | |

// Relaxing the monotonic descent requirement allows the algorithm to | |

// be more efficient in the long term at the cost of some local | |

// increase in the value of the objective function. | |

// | |

// This is because allowing for non-decreasing objective function | |

// values in a principled manner allows the algorithm to "jump over | |

// boulders" as the method is not restricted to move into narrow | |

// valleys while preserving its convergence properties. | |

// | |

// The parameter max_consecutive_nonmonotonic_steps controls the | |

// window size used by the step selection algorithm to accept | |

// non-monotonic steps. Setting this parameter to zero, recovers the | |

// classic monotonic descent algorithm. | |

// | |

// Based on algorithm 10.1.2 (page 357) of "Trust Region | |

// Methods" by Conn Gould & Toint, or equations 33-40 of | |

// "Non-monotone trust-region algorithms for nonlinear | |

// optimization subject to convex constraints" by Phil Toint, | |

// Mathematical Programming, 77, 1997. | |

// | |

// Example usage: | |

// | |

// TrustRegionStepEvaluator* step_evaluator = ... | |

// | |

// cost = ... // Compute the non-linear objective function value. | |

// model_cost_change = ... // Change in the value of the trust region objective. | |

// if (step_evaluator->StepQuality(cost, model_cost_change) > threshold) { | |

// x = x + delta; | |

// step_evaluator->StepAccepted(cost, model_cost_change); | |

// } | |

class TrustRegionStepEvaluator { | |

public: | |

// initial_cost is as the name implies the cost of the starting | |

// state of the trust region minimizer. | |

// | |

// max_consecutive_nonmonotonic_steps controls the window size used | |

// by the step selection algorithm to accept non-monotonic | |

// steps. Setting this parameter to zero, recovers the classic | |

// monotonic descent algorithm. | |

TrustRegionStepEvaluator(double initial_cost, | |

int max_consecutive_nonmonotonic_steps); | |

// Return the quality of the step given its cost and the decrease in | |

// the cost of the model. model_cost_change has to be positive. | |

double StepQuality(double cost, double model_cost_change) const; | |

// Inform the step evaluator that a step with the given cost and | |

// model_cost_change has been accepted by the trust region | |

// minimizer. | |

void StepAccepted(double cost, double model_cost_change); | |

private: | |

const int max_consecutive_nonmonotonic_steps_; | |

// The minimum cost encountered up till now. | |

double minimum_cost_; | |

// The current cost of the trust region minimizer as informed by the | |

// last call to StepAccepted. | |

double current_cost_; | |

double reference_cost_; | |

double candidate_cost_; | |

// Accumulated model cost since the last time the reference model | |

// cost was updated, i.e., when a step with cost less than the | |

// current known minimum cost is accepted. | |

double accumulated_reference_model_cost_change_; | |

// Accumulated model cost since the last time the candidate model | |

// cost was updated, i.e., a non-monotonic step was taken with a | |

// cost that was greater than the current candidate cost. | |

double accumulated_candidate_model_cost_change_; | |

// Number of steps taken since the last time minimum_cost was updated. | |

int num_consecutive_nonmonotonic_steps_; | |

}; | |

} // namespace internal | |

} // namespace ceres | |

#endif // CERES_INTERNAL_TRUST_REGION_STEP_EVALUATOR_H_ |