macop.algorithms.mono.HillClimberFirstImprovment¶
Hill Climber First Improvment algorithm starting from new solution and explore using neighborhood and loop over the best one obtained from neighborhood search space
Classes
|
Hill Climber First Improvment used as quick exploration optimisation algorithm |
-
class
macop.algorithms.mono.HillClimberFirstImprovment.HillClimberFirstImprovment(initalizer, evaluator, operators, policy, validator, maximise=True, parent=None)[source]¶ Hill Climber First Improvment used as quick exploration optimisation algorithm
This algorithm do a neighborhood exploration of a new generated solution (by doing operation on the current solution obtained) in order to find a better solution from the neighborhood space. Then replace the current solution by the first one from the neighbordhood space which is better than the current solution. Do these steps until a number of evaluation (stopping criterion) is reached.
-
initalizer¶ {function} – basic function strategy to initialize solution
-
evaluator¶ {function} – basic function in order to obtained fitness (mono or multiple objectives)
-
operators¶ {[Operator]} – list of operator to use when launching algorithm
-
policy¶ {Policy} – Policy class implementation strategy to select operators
-
validator¶ {function} – basic function to check if solution is valid or not under some constraints
-
maximise¶ {bool} – specify kind of optimisation problem
-
currentSolution¶ {Solution} – current solution managed for current evaluation
-
bestSolution¶ {Solution} – best solution found so far during running algorithm
-
callbacks¶ {[Callback]} – list of Callback class implementation to do some instructions every number of evaluations and load when initializing algorithm
-