Class DefiniteBitFlipMutation

All Implemented Interfaces:
Splittable<MutationOperator<BitVector>>, IterableMutationOperator<BitVector>, MutationOperator<BitVector>, UndoableMutationOperator<BitVector>

public final class DefiniteBitFlipMutation extends Object implements UndoableMutationOperator<BitVector>, IterableMutationOperator<BitVector>
DefiniteBitFlipMutation implements a variation of Bit Flip Mutation. The form of bit flip mutation commonly used in genetic algorithms (and implemented in the class BitFlipMutation) is not guaranteed to change any bits during a mutation. For a metaheuristic that operates on a single solution rather than a population of solutions, such as simulated annealing and hill climbers, where we might use a mutation operator to generate neighbors, then we will want mutation to always make some change. The DefiniteBitFlipMutation class is a variation of the classic bit flip that guarantees at least 1 bit will be flipped during each invocation of the mutation operator.

Genetic Algorithm style Bit Flip Mutation: In a bit flip mutation, each bit is flipped with probability M, known as the mutation rate. Flipping a bit means changing it to 0 if it is currently a 1, or changing it to 1 if it is currently a 0. If the length of the BitVector is N, then the expected number of bits flipped during a single mutation operation is NM. However, there is no guarantee that any bits will be flipped during a genetic algorithm style bit flip mutation. This behavior is fine for genetic algorithms, but may be less than desirable for other metaheuristics, such as those that operate on a single candidate solution rather than a population of them.

Definite Bit Flip Mutation: This class does not implement the genetic algorithm style bit flip mutation. Instead, it implements a variation of it that we call Definite Bit Flip, which guarantees that at least 1 bit will be flipped during a call to the mutate( method. Instead of a mutation parameter, the Definite Bit Flip Mutation uses a parameter B which is an upper bound on the number of bits that can be flipped during a single call to the mutate( method. When the mutate( method is called, the mutation operator picks a number of bits to flip, f, uniformly at random from the interval [1, B]. It then flips f randomly selected bits, where all combinations of f bits are equally likely. The expected number of bits flipped during a single call to the mutate( method is (1+B)/2.

  • Constructor Details

  • Method Details

    • mutate

      public void mutate(BitVector c)
      Description copied from interface: MutationOperator
      Mutates a candidate solution to a problem, by randomly modifying its state. The mutant that is produced is in the local neighborhood of the original candidate solution.
      Specified by:
      mutate in interface MutationOperator<BitVector>
      c - The candidate solution subject to the mutation. This method changes the state of c.
    • undo

      public void undo(BitVector c)
      Description copied from interface: UndoableMutationOperator
      Returns a candidate solution to its previous state prior to the most recent mutation performed.

      For example, consider the following. Let c' be the current state of c. Let c'' be the state of c after mutate(c); If we then call undo(c), the state of c should revert back to c'.

      The behavior of undo is undefined if c is altered by some other process between the calls to mutate and undo. The behavior is also undefined if a different candidate is given to undo then the last given to mutate. For example, if the following two statements are executed, mutate(c); undo(d);, the effect on d is undefined as it wasn't the most recently mutated candidate solution.

      Specified by:
      undo in interface UndoableMutationOperator<BitVector>
      c - The candidate solution to revert.
    • split

      public DefiniteBitFlipMutation 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 IterableMutationOperator<BitVector>
      Specified by:
      split in interface Splittable<MutationOperator<BitVector>>
      Specified by:
      split in interface UndoableMutationOperator<BitVector>
      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.
    • iterator

      public MutationIterator iterator(BitVector c)
      Description copied from interface: IterableMutationOperator
      Creates and returns a MutationIterator that can be used to systematically iterate over all of the direct neighbors (i.e., a single mutation step away) of a candidate solution, as one might do in a hill climber.
      Specified by:
      iterator in interface IterableMutationOperator<BitVector>
      c - The candidate solution subject to the mutation. Calling methods of the MutationIterator that is returned changes the state of that candidate solution. See the documentation of those methods for details of how such changes may occur.
      A MutationIterator for iterating over the direct neighbors of a candidate solution.