Uses of Package
org.cicirello.search

Packages that use 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.
  • Class
    Description
    This 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 self-determined, 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 self-determined, 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.
  • Class
    Description
    This 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.
  • Class
    Description
    This 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 single-solution metaheuristics, i.e., metaheuristics such as simulated annealing that operate one a single candidate solution (as compared to population-based 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.
  • Class
    Description
    This 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 self-determined, 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 self-determined, 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.
  • Class
    Description
    This interface defines the required methods for implementations of simple metaheuristics whose run length is self-determined, such as hill climbers that terminate upon reaching a local optima.
  • Class
    Description
    An object of this class encapsulates a solution with its corresponding cost value.
  • Class
    Description
    This 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.
  • Class
    Description
    This 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 self-determined, such as hill climbers that terminate upon reaching a local optima.
    This interface defines the required methods for implementations of single-solution metaheuristics, i.e., metaheuristics such as simulated annealing that operate one a single candidate solution (as compared to population-based 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.
  • Class
    Description
    This 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 self-determined, 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.