Class IterativeSampling<T extends Copyable<T>>
 Type Parameters:
T
 The type of object under optimization.
 All Implemented Interfaces:
Splittable<TrackableSearch<T>>
,Metaheuristic<T>
,SimpleMetaheuristic<T>
,TrackableSearch<T>
Iterative sampling is the simplest possible form of a stochastic sampling search. In iterative sampling, the search generates N random candidate solutions to the problem, each sampled uniformly at random from the space of possible solutions. It evaluates each of the N candidate solutions with respect to the optimization problem's cost function, and returns the best of the N candidate solutions.
For an early empirical comparison of iterative sampling with systematic search
algorithms, see:
P. Langley. Systematic and nonsystematic search strategies.
Proceedings of the First International Conference on Artificial Intelligence
Planning Systems, pages 145–152, 1992.

Constructor Summary
ConstructorDescriptionIterativeSampling
(IntegerCostOptimizationProblem<T> problem, Initializer<T> initializer) Constructs an iterative sampling search for a integervalued optimization problem.IterativeSampling
(IntegerCostOptimizationProblem<T> problem, Initializer<T> initializer, ProgressTracker<T> tracker) Constructs an iterative sampling search for a integervalued optimization problem.IterativeSampling
(OptimizationProblem<T> problem, Initializer<T> initializer) Constructs an iterative sampling search for a realvalued optimization problem.IterativeSampling
(OptimizationProblem<T> problem, Initializer<T> initializer, ProgressTracker<T> tracker) Constructs an iterative sampling search for a realvalued optimization problem. 
Method Summary
Modifier and TypeMethodDescriptionGets a reference to the problem that this search is solving.final ProgressTracker<T>
Gets theProgressTracker
object that is in use for tracking search progress.final long
Gets the total run length of the metaheuristic.final SolutionCostPair<T>
optimize()
Executes a single run of a metaheuristic whose run length cannot be specified (e.g., a hill climber that terminates when it reaches a local optima, or a stochastic sampler that terminates when it constructs one solution, etc).final SolutionCostPair<T>
optimize
(int numSamples) Generates multiple stochastic heuristic samples.final void
setProgressTracker
(ProgressTracker<T> tracker) Sets theProgressTracker
object that is in use for tracking search progress.split()
Generates a functionally identical copy of this object, for use in multithreaded implementations of search algorithms.

Constructor Details

IterativeSampling
public IterativeSampling(OptimizationProblem<T> problem, Initializer<T> initializer, ProgressTracker<T> tracker) Constructs an iterative sampling search for a realvalued optimization problem. Parameters:
problem
 An instance of an optimization problem to solve.initializer
 The source of random solutions.tracker
 A ProgressTracker object, which is used to keep track of the best solution found during the run, the time when it was found, and other related data. Throws:
NullPointerException
 if any of the parameters are null.

IterativeSampling
public IterativeSampling(IntegerCostOptimizationProblem<T> problem, Initializer<T> initializer, ProgressTracker<T> tracker) Constructs an iterative sampling search for a integervalued optimization problem. Parameters:
problem
 An instance of an optimization problem to solve.initializer
 The source of random solutions.tracker
 A ProgressTracker object, which is used to keep track of the best solution found during the run, the time when it was found, and other related data. Throws:
NullPointerException
 if any of the parameters are null.

IterativeSampling
Constructs an iterative sampling search for a realvalued optimization problem. AProgressTracker
is created for you. Parameters:
problem
 An instance of an optimization problem to solve.initializer
 The source of random solutions. Throws:
NullPointerException
 if any of the parameters are null.

IterativeSampling
Constructs an iterative sampling search for a integervalued optimization problem. AProgressTracker
is created for you. Parameters:
problem
 An instance of an optimization problem to solve.initializer
 The source of random solutions. Throws:
NullPointerException
 if any of the parameters are null.


Method Details

split
Description copied from interface:Splittable
Generates a functionally identical copy of this object, for use in multithreaded implementations of search algorithms. The state of the object that is returned may or may not be identical to that of the original. Thus, this is a distinct concept from the functionality of theCopyable
interface. Classes that implement this interface must ensure that the object returned performs the same functionality, and that it does not share any state data that would be either unsafe or inefficient for concurrent access by multiple threads. The split method is allowed to simply return the this reference, provided that it is both safe and efficient for multiple threads to share a single copy of the Splittable object. The intention is to provide a multithreaded search with the capability to provide spawned threads with their own distinct search operators. Such multithreaded algorithms can call the split method for each thread it spawns to generate a functionally identical copy of the operator, but with independent state. Specified by:
split
in interfaceMetaheuristic<T extends Copyable<T>>
 Specified by:
split
in interfaceSimpleMetaheuristic<T extends Copyable<T>>
 Specified by:
split
in interfaceSplittable<T extends Copyable<T>>
 Returns:
 A functionally identical copy of the object, or a reference to this if it is both safe and efficient for multiple threads to share a single instance of this Splittable object.

optimize
Description copied from interface:SimpleMetaheuristic
Executes a single run of a metaheuristic whose run length cannot be specified (e.g., a hill climber that terminates when it reaches a local optima, or a stochastic sampler that terminates when it constructs one solution, etc). If this method is called multiple times, each call is randomized in some algorithm dependent way (e.g., a hill climber begins at a new randomly generated starting solution), and reinitializes any control parameters that may have changed during the previous call to optimize to the start of run state.
 Specified by:
optimize
in interfaceSimpleMetaheuristic<T extends Copyable<T>>
 Returns:
 The current solution at the end of this run and its cost,
which may or may not be the same as the solution contained
in this metaheuristic's
ProgressTracker
, which contains the best of all runs. Returns null if the run did not execute, such as if the ProgressTracker already contains the theoretical best solution.

optimize
Generates multiple stochastic heuristic samples. Returns the best solution of the set of samples.
 Specified by:
optimize
in interfaceMetaheuristic<T extends Copyable<T>>
 Parameters:
numSamples
 The number of samples to perform. Returns:
 The best solution of this set of samples, which may or may not be the
same as the solution contained
in this search's
ProgressTracker
, which contains the best of all runs across all calls to the various optimize methods. Returns null if no runs executed, such as if the ProgressTracker already contains the theoretical best solution.

getProgressTracker
Description copied from interface:TrackableSearch
Gets theProgressTracker
object that is in use for tracking search progress. The object returned by this method contains the best solution found during the search (including across multiple concurrent runs if the search is multithreaded, or across multiple restarts if the run methods were called multiple times), as well as cost of that solution, among other information. See theProgressTracker
documentation for more information about the search data tracked by this object. Specified by:
getProgressTracker
in interfaceTrackableSearch<T extends Copyable<T>>
 Returns:
 the
ProgressTracker
in use by this metaheuristic.

setProgressTracker
Description copied from interface:TrackableSearch
Sets theProgressTracker
object that is in use for tracking search progress. Any previously set ProgressTracker is replaced by this one. Specified by:
setProgressTracker
in interfaceTrackableSearch<T extends Copyable<T>>
 Parameters:
tracker
 The new ProgressTracker to set. The tracker must not be null. This method does nothing if tracker is null.

getTotalRunLength
public final long getTotalRunLength()Description copied from interface:TrackableSearch
Gets the total run length of the metaheuristic. This is the total run length across all calls to the search. This may differ from what may be expected based on run lengths. For example, the search terminates if it finds the theoretical best solution, and also immediately returns if a prior call found the theoretical best. In such cases, the total run length may be less than the requested run length.
The meaning of run length may vary from one metaheuristic to another. Therefore, implementing classes should provide fresh documentation rather than relying entirely on the interface documentation.
 Specified by:
getTotalRunLength
in interfaceTrackableSearch<T extends Copyable<T>>
 Returns:
 the total run length of the metaheuristic

getProblem
Description copied from interface:TrackableSearch
Gets a reference to the problem that this search is solving. Specified by:
getProblem
in interfaceTrackableSearch<T extends Copyable<T>>
 Returns:
 a reference to the problem.
