GA_Minimizer.hh

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/// @file   core/optimization/GA_Minimizer.hh
/// @brief  Minimizer based on Genetic Algorithm
/// @author Sergey Lyskov

#ifndef INCLUDED_core_optimization_GA_Minimizer_hh
#define INCLUDED_core_optimization_GA_Minimizer_hh

// Package headers
#include <core/optimization/types.hh>
#include <core/optimization/MinimizerOptions.hh>
// AUTO-REMOVED #include <core/optimization/Multifunc.hh>

// AUTO-REMOVED #include <vector>

#include <core/optimization/Multifunc.fwd.hh>
#include <utility/vector1.hh>


namespace core {
namespace optimization {


/// Inner class for Genetic Algorithm, hold one population with some additional info
class EItem
{
public:
  EItem() {};
  EItem(const Multivec &vn) { v=vn; };

  Multivec v;  ///< item value
  char tag;  ///< tag for debug. (m-mutation, c-crossover, ...etc)
  double r;  ///< result of FF evaluation.

  // for sorting: compare function
  static inline bool sort_R_function(const EItem &e1, const EItem &e2) {return e1.r < e2.r;}
};


class GA_Minimizer
{
public:
  GA_Minimizer(Multifunc & func_in, MinimizerOptions const & options):
    func_( func_in ),
    add_original_(true),
    mutation_probability_( options.ga_mutation_probability() ),
    minimize_tolerance_( options.minimize_tolerance() )
  {}

  Real run( Multivec & phipsi_inout, int max_time); // starting position, and solution is returned here

private:
  EItem randomize(const EItem& sit, int &time);
  EItem loop(std::vector<EItem> & pop, int &time);
  void step(std::vector<EItem> &pop, int &c_time, int &mres, EItem &shift);


  /// genetic operators
  void mutate(EItem &);  // mutate given vector using normal random.
  void cross_over(EItem &V, EItem &A, EItem &B);

  Multifunc & func_;

  EItem best_;
  int allowed_time_;
  bool add_original_;  // add original best if shifting?

  Real min_error_;
  Real mutation_probability_;
  Real minimize_tolerance_;
};


} // namespace optimization
} // namespace core


#endif // INCLUDED_core_optimization_GA_Minimizer_hh