Package org.cicirello.search.problems

Package of classes and interfaces related to representing computational problems, as well as classes implementing a variety of specific computational problems.

Interface Summary

Interface	Description
IntegerCostOptimizationProblem<T extends Copyable<T>>	The IntegerCostOptimizationProblem interface provides search algorithms with a way to interact with an instance of an optimization problem without the need to know the specifics of the problem (e.g., traveling salesperson, bin packing, etc).
OptimizationProblem<T extends Copyable<T>>	The OptimizationProblem interface provides search algorithms with a way to interact with an instance of an optimization problem without the need to know the specifics of the problem (e.g., real-valued function optimization, traveling salesperson, bin packing, etc).
Problem<T extends Copyable<T>>	Base interface for all interfaces defining types of problems supported by the library.

Class Summary

Class	Description
BoundMax	The BoundMax class is an implementation of a generalization of the well-known OneMax problem, often used in benchmarking genetic algorithms and other metaheuristics.
CostFunctionScaler<T extends Copyable<T>>	This is a wrapper class for OptimizationProblem objects that enables scaling all cost values by a positive constant.
IntegerCostFunctionScaler<T extends Copyable<T>>	This is a wrapper class for IntegerCostOptimizationProblem objects that enables scaling all cost values by a positive constant.
Mix	This class implements Ackley's Mix problem, an artificial landscape that is a mix of the OneMax, TwoMax, Trap, and Plateau problems, which provides for a landscape that combines all of the properties of these benchmarking problems.
OneMax	The OneMax class is an implementation of the well-known OneMax problem, often used in benchmarking genetic algorithms and other metaheuristics.
OneMaxAckley	The OneMaxAckley class is an implementation of the well-known OneMax problem, often used in benchmarking genetic algorithms and other metaheuristics.
PermutationInAHaystack	The Permutation in a Haystack is a family of optimization problems that can be parameterized to the various types of permutation problem (e.g., absolute versus relative positioning).
Plateaus	This class implements Ackley's Plateaus problem, an artificial search landscape over the space of bitstrings that is characterized by large flat regions known as plateaus.
PolynomialRootFinding	This class defines polynomial root finding as an optimization problem, enabling solving via simulated annealing or other metaheuristic optimization algorithms.
Porcupine	This class implements the Porcupine landscape (Ackley, 1985), which is a very rugged search landscape, with an exponential number of local optima.
Trap	This class implements Ackley's Trap function, which defines a fitness landscape with a single global optima, and a single sub-optimal local optima, such that most of the search landscape is within the attraction basin of the local optima.
TwoMax	This class implements the benchmarking problem known as TwoMax.
TwoMaxEqualPeaks	This class implements a variation of the benchmarking problem known as TwoMax.