CAStarAlgorithm.h

Go to the documentation of this file.

/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          http://www.mrpt.org/                          |
   |                                                                        |
   | Copyright (c) 2005-2018, Individual contributors, see AUTHORS file     |
   | See: http://www.mrpt.org/Authors - All rights reserved.                |
   | Released under BSD License. See details in http://www.mrpt.org/License |
   +------------------------------------------------------------------------+ */
#ifndef CASTARALGORITHM_H
#define CASTARALGORITHM_H
#include <map>
#include <vector>
#include <cmath>
#include <mrpt/system/CTicTac.h>
 
namespace mrpt
{
namespace graphs
{
/** This class is intended to efficiently solve graph-search problems using
 * heuristics to determine the best path. To use it, a solution class must be
 * defined
  * so that it contains all the information about any partial or complete
 * solution. Then, a class inheriting from CAStarAlgorithm<Solution class> must
 * also be
  * implemented, overriding five virtual methods which define the behaviour of
 * the solutions. These methods are isSolutionEnded, isSolutionValid,
  * generateChildren, getHeuristic and getCost.
  * Once both classes are generated, each object of the class inheriting from
 * CAStarAlgorithm represents a problem who can be solved by calling
  * getOptimalSolution. See http://en.wikipedia.org/wiki/A*_search_algorithm for
 * details about how this algorithm works.
  * \sa CAStarAlgorithm::isSolutionEnded
  * \sa CAStarAlgorithm::isSolutionValid
  * \sa CAStarAlgorithm::generateChildren
  * \sa CAStarAlgorithm::getHeuristic
  * \sa CAStarAlgorithm::getCost
  * \ingroup mrpt_graphs_grp
  */
template <typename T>
class CAStarAlgorithm
{
   public:
        /**
          * Client code must implement this method.
          * Returns true if the given solution is complete.
          */
        virtual bool isSolutionEnded(const T& sol) = 0;
        /**
          * Client code must implement this method.
          * Returns true if the given solution is acceptable, that is, doesn't
         * violate the problem logic.
          */
        virtual bool isSolutionValid(const T& sol) = 0;
        /**
          * Client code must implement this method.
          * Given a partial solution, returns all its children solution, regardless
         * of their validity or completeness.
          */
        virtual void generateChildren(const T& sol, std::vector<T>& sols) = 0;
        /**
          * Client code must implement this method.
          * Given a partial solution, estimates the cost of the remaining (unknown)
         * part.
          * This cost must always be greater or equal to zero, and not greater than
         * the actual cost. Thus, must be 0 if the solution is complete.
          */
        virtual double getHeuristic(const T& sol) = 0;
        /**
          * Client code must implement this method.
          * Given a (possibly partial) solution, calculates its cost so far.
          * This cost must not decrease with each step. That is, a solution cannot
         * have a smaller cost than the previous one from which it was generated.
          */
        virtual double getCost(const T& sol) = 0;
 
   private:
        /**
          * Calculates the total cost (known+estimated) of a solution.
          */
        inline double getTotalCost(const T& sol)
        {
                return getHeuristic(sol) + getCost(sol);
        }
 
   public:
        /**
          * Finds the optimal solution for a problem, using the A* algorithm.
         * Returns whether an optimal solution was actually found.
          * Returns 0 if no solution was found, 1 if an optimal solution was found
         * and 2 if a (possibly suboptimal) solution was found but the time lapse
         * ended.
          */
        int getOptimalSolution(
                const T& initialSol, T& finalSol, double upperLevel = HUGE_VAL,
                double maxComputationTime = HUGE_VAL)
        {
                // Time measuring object is defined.
                mrpt::system::CTicTac time;
                time.Tic();
                // The partial solution set is initialized with a single element (the
                // starting solution).
                std::multimap<double, T> partialSols;
                partialSols.insert(
                        std::pair<double, T>(getTotalCost(initialSol), initialSol));
                // The best known solution is set to the upper bound (positive infinite,
                // if there is no given parameter).
                double currentOptimal = upperLevel;
                bool found = false;
                std::vector<T> children;
                // Main loop. Each iteration checks an element of the set, with minimum
                // estimated cost.
                while (!partialSols.empty())
                {
                        // Return if elapsed time has been reached.
                        if (time.Tac() >= maxComputationTime) return found ? 2 : 0;
                        typename std::multimap<double, T>::iterator it =
                                partialSols.begin();
                        double tempCost = it->first;
                        // If the minimum estimated cost is higher than the upper bound,
                        // then also is every solution in the set. So the algorithm returns
                        // immediately.
                        if (tempCost >= currentOptimal) return found ? 1 : 0;
                        T tempSol = it->second;
                        partialSols.erase(it);
                        // At this point, the solution cost is lesser than the upper bound.
                        // So, if the solution is complete, the optimal solution and the
                        // upper bound are updated.
                        if (isSolutionEnded(tempSol))
                        {
                                currentOptimal = tempCost;
                                finalSol = tempSol;
                                found = true;
                                continue;
                        }
                        // If the solution is not complete, check for its children. Each one
                        // is included in the set only if it's valid and it's not yet
                        // present in the set.
                        generateChildren(tempSol, children);
                        for (typename std::vector<T>::const_iterator it2 = children.begin();
                                 it2 != children.end(); ++it2)
                                if (isSolutionValid(*it2))
                                {
                                        bool alreadyPresent = false;
                                        double cost = getTotalCost(*it2);
                                        typename std::pair<
                                                typename std::multimap<double, T>::const_iterator,
                                                typename std::multimap<double, T>::const_iterator>
                                                range = partialSols.equal_range(cost);
                                        for (typename std::multimap<double, T>::const_iterator it3 =
                                                         range.first;
                                                 it3 != range.second; ++it3)
                                                if (it3->second == *it2)
                                                {
                                                        alreadyPresent = true;
                                                        break;
                                                }
                                        if (!alreadyPresent)
                                                partialSols.insert(
                                                        std::pair<double, T>(getTotalCost(*it2), *it2));
                                }
                }
                // No more solutions to explore...
                return found ? 1 : 0;
        }
};
}
}  // End of namespaces
#endif