Public Member Functions | |
| virtual int | isfeasible (Move *move) |
| virtual int | configurationmove (OpProblem *problem, Configuration *configuration) |
| int | test_bestfound (Move *move) |
Public Attributes | |
| int | walklength |
| NeighborhoodSearch * | nbhsearch |
| Metaheuristic * | mheur |
| int | nhtries |
| int | nbmoves |
 Public Attributes inherited from IncompleteAlgorithm | |
| Long | threshold |
Detailed Description
The class of local search algorithm on one particle : the random walk is parameterized with the walk lengh,a neighborhood and a metaheuristics
Member Function Documentation
◆ configurationmove()
|
virtual |
Neighborhood exploration algorithm for selecting and do a move from the current configuration : returns 1 if a move has been done and 0 if no move has been done
References OpProblem::best_config, OpProblem::bestmove, OpProblem::compute_var_conflict(), Configuration::copy_element(), Move::copymove(), OpProblem::currentmove, OpProblem::firstmove, OpProblem::move_execution(), OpProblem::next_move(), and Configuration::update_conflicts().
Referenced by GWWAlgorithm::randomwalk().
◆ isfeasible()
|
virtual |
feasability of a move (under or at threshold level pour GWW walks)
References OpProblem::lower_bound, GWWAlgorithm::randomwalk(), IncompleteAlgorithm::threshold, and Configuration::valuation.
◆ test_bestfound()
| int LSAlgorithm::test_bestfound | ( | Move * | move | ) |
test if a global best configuration has been found (returns 1 in that case)
References IncompleteAlgorithm::threshold.
Member Data Documentation
◆ mheur
| Metaheuristic* LSAlgorithm::mheur |
the metaheuristics used
◆ nbhsearch
| NeighborhoodSearch* LSAlgorithm::nbhsearch |
the way the neighborhood is explored
◆ nbmoves
| int LSAlgorithm::nbmoves |
number of moves done
Referenced by GWWAlgorithm::populationrandomwalk().
◆ nhtries
| int LSAlgorithm::nhtries |
number of move tries (for statistics)
Referenced by GWWAlgorithm::populationrandomwalk().
◆ walklength
| int LSAlgorithm::walklength |
walk length
Referenced by GWWAlgorithm::randomwalk().
