Problem (Chips-n-Salsa - A Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms)

Type Parameters:

T - The type of object used to represent candidate solutions to the problem.

All Known Subinterfaces:

IntegerCostOptimizationProblem<T>, OptimizationProblem<T>, SingleMachineSchedulingProblem

All Known Implementing Classes:

BaseTSP, BinPacking, BinPacking.Triplet, BinPacking.UniformRandom, BoundMax, CostFunctionScaler, ForresterEtAl2008, GramacyLee2012, HollandRoyalRoad, IntegerCostFunctionScaler, LargestCommonSubgraph, MinimizeMakespan, MinimizeMaximumFlowtime, MinimizeMaximumLateness, MinimizeMaximumTardiness, Mix, OneMax, OneMaxAckley, PermutationInAHaystack, PermutationToBitVectorProblem.DoubleCost, PermutationToBitVectorProblem.IntegerCost, Plateaus, PolynomialRootFinding, Porcupine, QuadraticAssignmentProblem, RandomTSPMatrix, RandomTSPMatrix.Double, RandomTSPMatrix.Integer, RoyalRoad, Trap, TSP, TSP.Double, TSP.DoubleMatrix, TSP.Integer, TSP.IntegerMatrix, TwoMax, TwoMaxEqualPeaks, WeightedEarlinessTardiness, WeightedFlowtime, WeightedLateness, WeightedNumberTardyJobs, WeightedSquaredTardiness, WeightedTardiness
```
public interface Problem<T extends Copyable<T>>
```
Base interface for all interfaces defining types of problems supported by the library.

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`double`	`costAsDouble(T candidate)`	Computes the cost of a candidate solution to the problem instance.
`SolutionCostPair<T>`	`getSolutionCostPair(T candidate)`	Computes the cost of a candidate solution to the problem instance.

- Method Detail
  - getSolutionCostPair
```
SolutionCostPair<T> getSolutionCostPair(T candidate)
```
    Computes the cost of a candidate solution to the problem instance. The lower the cost, the more optimal the candidate solution.
    
    Parameters:
    
    candidate - The candidate solution to evaluate.
    
    Returns:
    
    A SolutionCostPair object containing the candidate solution and the cost of that candidate solution. Lower cost means better solution.
  - costAsDouble
```
double costAsDouble(T candidate)
```
    Computes the cost of a candidate solution to the problem instance. The lower the cost, the more optimal the candidate solution. Note that subinterfaces provide methods for computing the cost as more specific types (e.g., as an int).
    
    Parameters:
    
    candidate - The candidate solution to evaluate.
    
    Returns:
    
    The cost of the candidate solution as a value of type double. Lower cost means better solution.