createRandomRestartStochasticHillClimbingSolver

fun createRandomRestartStochasticHillClimbingSolver(problemDefinition: ProblemDefinition, modelBuilder: ModelBuilderIfc, maxNumRestarts: Int = defaultMaxRestarts, startingPoint: MutableMap<String, Double>? = null, maxIterations: Int = defaultMaxNumberIterations, replicationsPerEvaluation: Int = defaultReplicationsPerEvaluation, solutionCache: SolutionCacheIfc = MemorySolutionCache(), simulationRunCache: SimulationRunCacheIfc? = null, experimentRunParameters: ExperimentRunParametersIfc? = null, defaultKSLDatabaseObserverOption: Boolean = false): RandomRestartSolver(source)

Creates and configures a simulated annealing optimization algorithm for a given problem definition.

Return

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

Parameters

problemDefinition

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

modelBuilder

The model builder interface used to create models for evaluation.

maxNumRestarts

The maximum number of restarts to be performed.

startingPoint

An optional starting point. If provided, the FIRST run of the solver will begin here. All subsequent restarts will begin at purely random, auto-generated coordinates

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).

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.