Uses of Package
org.cicirello.search
Package
Description
This package includes classes and interfaces related to implementing metaheuristic search
algorithms in general, rather than specific to a particular metaheuristic.
This package includes multithreaded search implementations, as well as classes and interfaces
related to implementing multithreaded metaheuristics.
This package includes classes and interfaces directly related to implementing evolutionary
algorithms.
This package includes classes and interfaces directly related to implementing hill climbers.
This package includes classes and interfaces for defining various operators required by simulated
annealing and other metaheuristics, such as mutation operators, along with other related classes
and interfaces.
Package of classes and interfaces related to representing computational problems, as well as
classes implementing a variety of specific computational problems.
This package includes classes and interfaces related to implementing multistart metaheuristics
(i.e., metaheuristics that periodically restart, and return the best solution across a number of
such restarts).
This package includes classes and interfaces directly related to implementing simulated
annealing.
This package includes classes and interfaces directly related to implementing stochastic sampling
algorithms.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of metaheuristics, for which the maximum run length can be specified, and which have the capability of restarting from a previously optimized solution.This interface defines the required methods for implementations of simple metaheuristics that locally optimize from some initial solution (random or otherwise) whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.This interface defines the required methods for implementations of simple metaheuristics whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.An object of this class encapsulates a solution with its corresponding cost value.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of metaheuristics, for which the maximum run length can be specified, and which have the capability of restarting from a previously optimized solution.An object of this class encapsulates a solution with its corresponding cost value.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of metaheuristics, for which the maximum run length can be specified, and which have the capability of restarting from a previously optimized solution.This interface defines the required methods for implementations of singlesolution metaheuristics, i.e., metaheuristics such as simulated annealing that operate one a single candidate solution (as compared to populationbased metaheuristics such as genetic algorithms.An object of this class encapsulates a solution with its corresponding cost value.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of simple metaheuristics that locally optimize from some initial solution (random or otherwise) whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.This interface defines the required methods for implementations of simple metaheuristics whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.

ClassDescriptionThis interface defines the required methods for implementations of simple metaheuristics whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.

ClassDescriptionAn object of this class encapsulates a solution with its corresponding cost value.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of metaheuristics, for which the maximum run length can be specified, and which have the capability of restarting from a previously optimized solution.An object of this class encapsulates a solution with its corresponding cost value.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of metaheuristics, for which the maximum run length can be specified, and which have the capability of restarting from a previously optimized solution.This interface defines the required methods for implementations of simple metaheuristics that locally optimize from some initial solution (random or otherwise) whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.This interface defines the required methods for implementations of singlesolution metaheuristics, i.e., metaheuristics such as simulated annealing that operate one a single candidate solution (as compared to populationbased metaheuristics such as genetic algorithms.An object of this class encapsulates a solution with its corresponding cost value.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.

ClassDescriptionThis interface defines the required methods for implementations of metaheuristics, in particular metaheuristics for which the maximum run length can be specified.This class is used to track search algorithm progress, and supports multithreaded search algorithms.This interface defines the required methods for implementations of simple metaheuristics whose run length is selfdetermined, such as hill climbers that terminate upon reaching a local optima.An object of this class encapsulates a solution with its corresponding cost value.This interface defines the required functionality of search algorithm implementations that support tracking search progress across multiple runs, whether multiple sequential runs, or multiple concurrent runs in the case of a parallel metaheuristic.