crossEntropySolver

fun crossEntropySolver(problemDefinition: ProblemDefinition, modelBuilder: ModelBuilderIfc, ceSampler: CESamplerIfc = CENormalSampler(problemDefinition), startingPoint: MutableMap<String, Double>? = null, maxIterations: Int = defaultMaxNumberIterations, replicationsPerEvaluation: Int = defaultReplicationsPerEvaluation, solutionCache: SolutionCacheIfc = MemorySolutionCache(), simulationRunCache: SimulationRunCacheIfc? = null, printer: (Solver) -> Unit? = null, experimentRunParameters: ExperimentRunParametersIfc? = null, defaultKSLDatabaseObserverOption: Boolean = false): CrossEntropySolver(source)

Creates and configures a cross-entropy optimization algorithm for a given problem definition.

An instance of CrossEntropySolver that encapsulates the optimization process and results.

problemDefinition

The definition of the optimization problem, including constraints and objectives.

modelBuilder

The model builder interface used to create models for evaluation.

startingPoint

Optional initial solution to start the optimization. Defaults to the starting point provided by the problem definition.

ceSampler

The cross-entropy sampler. By default, it is CENormalSampler

maxIterations

The maximum number of iterations the algorithm will run. Defaults to 1000.

replicationsPerEvaluation

The number of replications to use during each evaluation to reduce stochastic noise. Defaults to 50.

solutionCache

Specifies if the evaluator uses a solution cache. By default, this is MemorySolutionCache.

simulationRunCache

Specifies if the simulation oracle will use a SimulationRunCache. The default is null (no cache).

printer

Optional callback function to print or handle intermediate solutions. Can be used to observe the optimization process.

experimentRunParameters

the run parameters to apply to the model during the building process

defaultKSLDatabaseObserverOption

indicates if a default KSL database should be created and attached to the model. The default is false.