Module org.cicirello.chips_n_salsa
Package org.cicirello.search.operators.reals

Class RealVectorInitializer

java.lang.Object
org.cicirello.search.operators.reals.RealVectorInitializer
All Implemented Interfaces:
Splittable<Initializer<RealVector>>, Initializer<RealVector>
public final class RealVectorInitializer extends Object implements Initializer<RealVector>
Generates random RealVector objects for use in generating random initial solutions for simulated annealing and other metaheuristics, and for copying such objects. This initializer supports both unbounded vectors (RealVector) as well as bounded vectors, where the domain of values is bound in an interval. In the bounded case, the objects created by this class enforce the bounds upon calls to RealVector.set(int, double) such that the RealVector.set(int, double) method will set the value to the min if a value is passed less than min (and similarly for max).

  • Constructor Summary

    Constructors
    Constructor
    Description
    RealVectorInitializer(double[] a, double[] b)
    Construct a RealVectorInitializer that generates random solutions such that the values of variable i is chosen uniformly in the interval [a[i], b[i]).
    RealVectorInitializer(double[] a, double[] b, double[] min, double[] max)
    Construct a RealVectorInitializer that generates random solutions such that the values of variable i is chosen uniformly in the interval [a[i], b[i]), subject to bounds [min[i], max[i]].
    RealVectorInitializer(double[] a, double[] b, double min, double max)
    Construct a RealVectorInitializer that generates random solutions such that the values of variable i is chosen uniformly in the interval [a[i], b[i]), subject to bounds [min, max].
    RealVectorInitializer(int n, double a, double b)
    Construct a RealVectorInitializer that generates random solutions such that the values of all n variables are chosen uniformly in the interval [a, b).
    RealVectorInitializer(int n, double a, double b, double min, double max)
    Construct a RealVectorInitializer that generates random solutions such that the values of all n variables are chosen uniformly in the interval [a, b), subject to bounds [min, max].

  • Method Summary

    Modifier and Type
    Method
    Description
    final RealVector
    createCandidateSolution()
    Creates one candidate solution to a problem.
    RealVectorInitializer
    split()
    Generates a functionally identical copy of this object, for use in multithreaded implementations of search algorithms.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Constructor Details

    • RealVectorInitializer

      public RealVectorInitializer(int n, double a, double b)
      Construct a RealVectorInitializer that generates random solutions such that the values of all n variables are chosen uniformly in the interval [a, b). The RealVector objects returned by the createCandidateSolution() method are otherwise unbounded (i.e., future mutations may alter the values such that it leaves that interval). Use a different constructor if you need to enforce bounds.
      Parameters:
      n - The number of input variables for the function.
      a - The lower end of the interval (inclusive).
      b - The upper end of the interval (exclusive).
      Throws:
      IllegalArgumentException - if a ≥ b
      NegativeArraySizeException - if n < 0

    • RealVectorInitializer

      public RealVectorInitializer(double[] a, double[] b)
      Construct a RealVectorInitializer that generates random solutions such that the values of variable i is chosen uniformly in the interval [a[i], b[i]). The RealVector objects returned by the createCandidateSolution() method are otherwise unbounded (i.e., future mutations may alter the values such that it leaves that interval). Use a different constructor if you need to enforce bounds.
      Parameters:
      a - An array of the left points of the intervals, inclusive. The length of this array corresponds to the number of input variables for the function you are optimizing. Variable x[i]'s initial value will be at least a[i].
      b - An array of the right points of the intervals, exclusive. The length of this array corresponds to the number of input variables for the function you are optimizing. Variable x[i]'s initial value will be less than b[i].
      Throws:
      IllegalArgumentException - if the lengths of a and b are different, or if there exists an i, such that a[i] ≥ b[i].

    • RealVectorInitializer

      public RealVectorInitializer(int n, double a, double b, double min, double max)
      Construct a RealVectorInitializer that generates random solutions such that the values of all n variables are chosen uniformly in the interval [a, b), subject to bounds [min, max]. If this constructor is used, then the createCandidateSolution() method will return an object of a subclass of RealVector, which will enforce the constraint that the values of the function inputs must remain in the interval [min, max] as mutation and other operators are applied.
      Parameters:
      n - The number of input variables for the function.
      a - The lower end of the interval (inclusive).
      b - The upper end of the interval (exclusive).
      min - Lower bound on allowed values for the function inputs generated.
      max - Upper bound on allowed values for the function inputs generated.
      Throws:
      IllegalArgumentException - if a ≥ b or if min > max
      NegativeArraySizeException - if n < 0

    • RealVectorInitializer

      public RealVectorInitializer(double[] a, double[] b, double min, double max)
      Construct a RealVectorInitializer that generates random solutions such that the values of variable i is chosen uniformly in the interval [a[i], b[i]), subject to bounds [min, max]. If this constructor is used, then the createCandidateSolution() method will return an object of a subclass of RealVector, which will enforce the constraint that the values of the function inputs must remain in the interval [min, max] as mutation and other operators are applied.
      Parameters:
      a - An array of the left points of the intervals, inclusive. The length of this array corresponds to the number of input variables for the function you are optimizing. Variable x[i]'s initial value will be at least a[i].
      b - An array of the right points of the intervals, exclusive. The length of this array corresponds to the number of input variables for the function you are optimizing. Variable x[i]'s initial value will be less than b[i].
      min - Lower bound on allowed values for the function inputs generated.
      max - Upper bound on allowed values for the function inputs generated.
      Throws:
      IllegalArgumentException - if the lengths of a and b are different; or if there exists an i, such that a[i] ≥ b[i]; or if min > max.

    • RealVectorInitializer

      public RealVectorInitializer(double[] a, double[] b, double[] min, double[] max)
      Construct a RealVectorInitializer that generates random solutions such that the values of variable i is chosen uniformly in the interval [a[i], b[i]), subject to bounds [min[i], max[i]]. If this constructor is used, then the createCandidateSolution() method will return an object of a subclass of RealVector, which will enforce the constraint that the values of the function inputs must remain in the interval [min[i], max[i]] as mutation and other operators are applied.
      Parameters:
      a - An array of the left points of the intervals, inclusive. The length of this array corresponds to the number of input variables for the function you are optimizing. Variable x[i]'s initial value will be at least a[i].
      b - An array of the right points of the intervals, exclusive. The length of this array corresponds to the number of input variables for the function you are optimizing. Variable x[i]'s initial value will be less than b[i].
      min - An array of lower bounds on allowed values for the function inputs generated, such that x[i] will never be less than min[i].
      max - An array of upper bounds on allowed values for the function inputs generated, such that x[i] will never be greater than max[i].
      Throws:
      IllegalArgumentException - if the lengths of a and b are different; or if there exists an i, such that a[i] ≥ b[i] or min[i] > max[i].

  • Method Details

    • createCandidateSolution

      public final RealVector createCandidateSolution()
      Description copied from interface: Initializer
      Creates one candidate solution to a problem.
      Specified by:
      createCandidateSolution in interface Initializer<RealVector>
      Returns:
      a candidate solution to a problem instance.

    • split

      public RealVectorInitializer 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 the Copyable 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 interface Splittable<Initializer<RealVector>>
      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.