#ifndef LEMON_SIMANN_H

 #define LEMON_SIMANN_H

 #include <cstdlib>

 #include <cmath>

 #include <lemon/time_measure.h>

 namespace lemon {

   const double INFTY = 1e24;

   class SimAnnBase {

   public:

     class Controller;

   private:

     Controller *controller;

   protected:

     double curr_cost;

     double prev_cost;

     double best_cost;

     virtual void mutate() = 0;

     virtual void revert() = 0;

     virtual void saveAsBest() = 0;

   public:

     SimAnnBase() {

       curr_cost = prev_cost = best_cost = INFTY;

     }

     void setController(Controller &_controller) {

       controller = &_controller;

       controller->setBase(this);

     }

     double getCurrCost() const { return curr_cost; }

     double getPrevCost() const { return prev_cost; }

     double getBestCost() const { return best_cost; }

     void run() {

       controller->init();

       do {

         mutate();

         if (controller->accept()) {

           controller->acceptEvent();

           if (curr_cost < best_cost) {

             saveAsBest();

             controller->improveEvent();

           }

         }

         else {

           revert();

           controller->rejectEvent();

         }

       } while (controller->next());

     }

     /*! \brief A base class for controllers. */

     class Controller {

     public:

       SimAnnBase *base;

       virtual void init() {}

       /*! \brief This is called when a neighbouring state gets accepted. */

       virtual void acceptEvent() {}

       /*! \brief This is called when the accepted neighbouring state's cost is

        *  less than the best found one's.

        */

       virtual void improveEvent() {}

       /*! \brief This is called when a neighbouring state gets rejected. */

       virtual void rejectEvent() {}

       virtual void setBase(SimAnnBase *_base) { base = _base; }

       /*! */

       virtual bool next() = 0;

       /*! */

       virtual bool accept() = 0;

     };

   };

   /*! \todo atgondolni mi is ez a prev_cost */

   template <typename E>

   class SimAnn : public SimAnnBase {

   private:

     E *curr_ent;

     E *best_ent;

   public:

     SimAnn() : SimAnnBase() {}

     void setEntity(E &ent) {

       curr_ent = new E(ent);

       best_ent = new E(ent);

     }

     E getBestEntity() { return *best_ent; }

     void mutate() {

       prev_cost = curr_cost;

       curr_cost = curr_ent->mutate();

     }

     void revert() {

       curr_ent->revert();

       curr_cost = prev_cost;

     }

     void saveAsBest() {

       *best_ent = *curr_ent;

       best_cost = curr_cost;

     }

   };

   class EntitySkeleton {

   public:

     /*! \brief Makes a minor change to the entity.

      *  \return the new cost

      */

     double mutate() { return 0.0; }

     /*! \brief Restores the entity to its previous state i.e. reverts the

      *  effects of the last mutate.

      */

     void revert() {}

   };

   /*! \brief A simple controller for the simulated annealing class.

    *  \todo Find a way to set the various parameters.

    */

   class SimpleController : public SimAnnBase::Controller {

   public:

     long iter, last_impr, max_iter, max_no_impr;

     double temp, ann_fact;

     /*! \param _max_iter maximum number of iterations

      *  \param _max_no_impr maximum number of consecutive iterations which do

      *         not yield a better solution

      *  \param _temp initial temperature

      *  \param _ann_fact annealing factor

      */

     SimpleController(long _max_iter = 500000, long _max_no_impr = 20000,

     double _temp = 1000, double _ann_fact = 0.9999) : iter(0), last_impr(0),

     max_iter(_max_iter), max_no_impr(_max_no_impr), temp(_temp),

     ann_fact(_ann_fact) {}

     void acceptEvent() {

       iter++;

     }

     void improveEvent() {

       last_impr = iter;

     }

     void rejectEvent() {

       iter++;

     }

     bool next() {

       temp *= ann_fact;

       bool quit = (iter > max_iter) || (iter - last_impr > max_no_impr);

       return !quit;

     }

     bool accept() {

       double cost_diff = base->getPrevCost() - base->getCurrCost();

       if (cost_diff < 0.0) {

         return (drand48() <= exp(cost_diff / temp));

       }

       else {

         return true;

       }

     }

   };

   /*! \brief A controller with preset running time for the simulated annealing

    *  class.

    *  \todo Find a better name.

    */

   class AdvancedController : public SimAnnBase::Controller {

   private:

     Timer timer;

     /*! \param time the elapsed time in seconds */

     virtual double threshold(double time) {

       // this is the function 1 / log(x) scaled and offset

       static double xm = 5.0 / end_time;

       static double ym = start_threshold / (1 / log(1.2) - 1 / log(5.0 + 1.2));

       return ym * (1 / log(xm * time + 1.2) - 1 / log(5.0 + 1.2));

     }

   public:

     double alpha, beta, gamma;

     double end_time, start_time;

     double start_threshold;

     double avg_cost;

     double temp, ann_fact;

     bool warmup;

     long iter;

     /*! \param _end_time running time in seconds

      *  \param _alpha parameter used to calculate the running average

      *  \param _beta parameter used to decrease the annealing factor

      *  \param _gamma parameter used to increase the temperature

      */

     AdvancedController(double _end_time, double _alpha = 0.2,

     double _beta = 0.9, double _gamma = 1.2) : alpha(_alpha), beta(_beta),

     gamma(_gamma), end_time(_end_time), ann_fact(0.9999), warmup(true),

     iter(0) {}

     void init() {

       avg_cost = base->getCurrCost();

     }

     void acceptEvent() {

       avg_cost = alpha * base->getCurrCost() + (1.0 - alpha) * avg_cost;

       iter++;

     }

     void improveEvent() {

     }

     void rejectEvent() {

       iter++;

     }

     bool next() {

       if (warmup) {

         static double max_cost_diff = 0.0;

         double cost_diff = base->getCurrCost() - base->getPrevCost();

         // jo ez igy egyaltalan? -> prev_cost

         if ((cost_diff > 0.0) && (cost_diff > max_cost_diff)) {

           max_cost_diff = cost_diff;

         }

         // How to set the starting temperature when all the 100 first

         // iterations improve the solution?

         if (iter > 100) {

           // calculate starting threshold and starting temperature

           start_threshold = fabs(base->getBestCost() - avg_cost);

           temp = exp(max_cost_diff) / 0.5;

           warmup = false;

           timer.reset();

         }

         return true;

       }

       else {

         double elapsed_time = timer.getRealTime();

         if (fabs(avg_cost - base->getBestCost()) > threshold(elapsed_time)) {

           // decrease the annealing factor

           ann_fact *= beta;

         }

         else {

           // increase the temperature

           temp *= gamma;

         }

         temp *= ann_fact;

         return elapsed_time < end_time;

       }

     }

     bool accept() {

       if (warmup) {

         // we accept eveything during the "warm up" phase

         return true;

       }

       else {

         double cost_diff = base->getPrevCost() - base->getCurrCost();

         if (cost_diff < 0.0) {

           return (drand48() <= exp(cost_diff / temp));

         }

         else {

           return true;

         }

       }

     }

   };

 }

 #endif