Module org.cicirello.chips_n_salsa
Package org.cicirello.search.problems

Class CostFunctionScaler<T extends Copyable<T>>

java.lang.Object
org.cicirello.search.problems.CostFunctionScaler<T>
Type Parameters:
T - The type of object used to represent candidate solutions to the problem.
All Implemented Interfaces:
OptimizationProblem<T>, Problem<T>
public final class CostFunctionScaler<T extends Copyable<T>> extends Object implements OptimizationProblem<T>
This is a wrapper class for OptimizationProblem objects that enables scaling all cost values by a positive constant. This transformation doesn't change what solution is optimal, and doesn't change the topology of the search space. It simply scales the cost values. For example, if you want to explore the effects of the range of the cost function on the behavior of a search algorithm, you can use this class to scale the cost values of a problem whose cost function range is known.

Note that this does not scale the results of the value(T) method, which will continue to return the actual value of the candidate solution (see its documentation for details).

  • Constructor Details

    • CostFunctionScaler

      public CostFunctionScaler(OptimizationProblem<T> problem, double scale)
      Constructs the CostFunctionScaler.
      Parameters:
      problem - The original problem specification.
      scale - The scale factor, which must be positive. All cost values of the original problem will be multiplied by scale.
      Throws:
      IllegalArgumentException - if scale ≤ 0.

  • Method Details

    • cost

      public double cost(T candidate)
      Computes the cost of a candidate solution to the problem instance. The lower the cost, the more optimal the candidate solution.

      In the case of the CostFunctionScaler, the cost values are all multiplied by the scale factor.

      Specified by:
      cost in interface OptimizationProblem<T extends Copyable<T>>
      Parameters:
      candidate - The candidate solution to evaluate.
      Returns:
      The cost of the candidate solution. Lower cost means better solution.

    • minCost

      public double minCost()
      A lower bound on the minimum theoretical cost across all possible solutions to the problem instance, where lower cost implies better solution. The default implementation returns Double.NEGATIVE_INFINITY.

      In the case of the CostFunctionScaler, the cost values are all multiplied by the scale factor.

      Specified by:
      minCost in interface OptimizationProblem<T extends Copyable<T>>
      Returns:
      A lower bound on the minimum theoretical cost of the problem instance.

    • value

      public double value(T candidate)
      Description copied from interface: OptimizationProblem
      Computes the value of the candidate solution within the usual constraints and interpretation of the problem.
      Specified by:
      value in interface OptimizationProblem<T extends Copyable<T>>
      Parameters:
      candidate - The candidate solution to evaluate.
      Returns:
      The actual optimization value of the candidate solution.