Uses of Interface
org.cicirello.search.problems.IntegerCostOptimizationProblem

Packages that use IntegerCostOptimizationProblem

Package	Description
org.cicirello.search.evo	This package includes classes and interfaces directly related to implementing evolutionary algorithms.
org.cicirello.search.hc	This package includes classes and interfaces directly related to implementing hill climbers.
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.
org.cicirello.search.problems.binpack	Classes and interfaces related to the Bin Packing.
org.cicirello.search.problems.scheduling	Package of classes and interfaces related to representing and solving scheduling problems, which includes implementations of constructive heuristics for scheduling problems.
org.cicirello.search.problems.tsp	Classes and interfaces related to the Traveling Salesperson Problem (TSP).
org.cicirello.search.sa	This package includes classes and interfaces directly related to implementing simulated annealing.
org.cicirello.search.ss	This package includes classes and interfaces directly related to implementing stochastic sampling algorithms.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.evo

Methods in org.cicirello.search.evo that return IntegerCostOptimizationProblem

Modifier and Type	Method	Description
IntegerCostOptimizationProblem<T>	NegativeIntegerCostFitnessFunction.getProblem()

Constructors in org.cicirello.search.evo with parameters of type IntegerCostOptimizationProblem

Modifier	Constructor	Description
	InverseCostFitnessFunction(IntegerCostOptimizationProblem<T> problem)	Constructs a fitness function that transforms the cost of solution s to fitness with the following transformation: fitness(s) = 1.0 / (1.0 + problem.cost(s) - problem.minCost()).
	InverseCostFitnessFunction(IntegerCostOptimizationProblem<T> problem, double c)	Constructs a fitness function that transforms the cost of solution s to fitness with the following transformation: fitness(s) = c / (c + problem.cost(s) - problem.minCost()).
	NegativeIntegerCostFitnessFunction(IntegerCostOptimizationProblem<T> problem)	Constructs a fitness function that transforms the cost of solution s to fitness with the following transformation: fitness(s) = -cost(s).
	OnePlusOneEvolutionaryAlgorithm(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer)	Creates a OnePlusOneEvolutionaryAlgorithm instance for integer-valued optimization problems.
	OnePlusOneEvolutionaryAlgorithm(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, ProgressTracker<T> tracker)	Creates a OnePlusOneEvolutionaryAlgorithm instance for integer-valued optimization problems.
	OnePlusOneGeneticAlgorithm(IntegerCostOptimizationProblem<BitVector> problem, double m, int bitLength)	Creates a OnePlusOneGeneticAlgorithm instance for integer-valued optimization problems.
	OnePlusOneGeneticAlgorithm(IntegerCostOptimizationProblem<BitVector> problem, double m, int bitLength, ProgressTracker<BitVector> tracker)	Creates a OnePlusOneGeneticAlgorithm instance for integer-valued optimization problems.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.hc

Constructors in org.cicirello.search.hc with parameters of type IntegerCostOptimizationProblem

Modifier	Constructor	Description
	FirstDescentHillClimber(IntegerCostOptimizationProblem<T> problem, IterableMutationOperator<T> mutation, Initializer<T> initializer)	Constructs a first descent hill climber object for integer-valued optimization problem.
	FirstDescentHillClimber(IntegerCostOptimizationProblem<T> problem, IterableMutationOperator<T> mutation, Initializer<T> initializer, ProgressTracker<T> tracker)	Constructs a first descent hill climber object for integer-valued optimization problem.
	SteepestDescentHillClimber(IntegerCostOptimizationProblem<T> problem, IterableMutationOperator<T> mutation, Initializer<T> initializer)	Constructs a steepest descent hill climber object for integer-valued optimization problem.
	SteepestDescentHillClimber(IntegerCostOptimizationProblem<T> problem, IterableMutationOperator<T> mutation, Initializer<T> initializer, ProgressTracker<T> tracker)	Constructs a steepest descent hill climber object for integer-valued optimization problem.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.problems

Classes in org.cicirello.search.problems that implement IntegerCostOptimizationProblem

Modifier and Type	Class	Description
final class	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.
final class	IntegerCostFunctionScaler<T extends Copyable<T>>	This is a wrapper class for IntegerCostOptimizationProblem objects that enables scaling all cost values by a positive constant.
final class	LargestCommonSubgraph	This class is an implementation of the Largest Common Subgraph problem, an NP-Hard combinatorial optimization problem.
final class	OneMax	The OneMax class is an implementation of the well-known OneMax problem, often used in benchmarking genetic algorithms and other metaheuristics.
final class	OneMaxAckley	The OneMaxAckley class is an implementation of the well-known OneMax problem, often used in benchmarking genetic algorithms and other metaheuristics.
final class	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).
static final class	PermutationToBitVectorProblem.IntegerCost	This class implements a mapping between Permutation problems and BitVector problems, where cost values are of type int.
final class	Porcupine	This class implements the Porcupine landscape (Ackley, 1985), which is a very rugged search landscape, with an exponential number of local optima.
final class	QuadraticAssignmentProblem	This class is an implementation of the Quadratic Assignment Problem (QAP), an NP-Hard optimization problem.
final class	RoyalRoad	Implementation of the Royal Road problem of Mitchell, Forrest, and Holland, both the variation with stepping stones and the one without.
final class	TwoMax	This class implements the benchmarking problem known as TwoMax.
final class	TwoMaxEqualPeaks	This class implements a variation of the benchmarking problem known as TwoMax.

Constructors in org.cicirello.search.problems with parameters of type IntegerCostOptimizationProblem

Modifier	Constructor	Description
	IntegerCost(IntegerCostOptimizationProblem<Permutation> problem, int permutationLength)	Initializes the mapping between Permutation problem and BitVector problem for a specific permutation length.
	IntegerCostFunctionScaler(IntegerCostOptimizationProblem<T> problem, int scale)	Constructs the IntegerCostFunctionScaler.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.problems.binpack

Classes in org.cicirello.search.problems.binpack that implement IntegerCostOptimizationProblem

Modifier and Type	Class	Description
class	BinPacking	This class, and its nested classes, implements the Bin Packing problem.
static final class	BinPacking.Triplet	Generates instances of the Bin Packing problem where the optimal solution is comprised of all full triplet bins (each bin in optimal solution has exactly 3 items that fills the bin to capacity).
static final class	BinPacking.UniformRandom	Generates instances of the Bin Packing problem with item sizes that are generated uniformly at random.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.problems.scheduling

Subinterfaces of IntegerCostOptimizationProblem in org.cicirello.search.problems.scheduling

Modifier and Type	Interface	Description
interface	SingleMachineSchedulingProblem	Implement this interface to define a single machine scheduling problem.

Classes in org.cicirello.search.problems.scheduling that implement IntegerCostOptimizationProblem

Modifier and Type	Class	Description
final class	MinimizeMakespan	Implements the common scheduling cost function known as makespan.
final class	MinimizeMaximumFlowtime	Implements the scheduling cost function known as maximum flowtime (which we want to minimize).
final class	MinimizeMaximumLateness	Implements the scheduling cost function known as maximum lateness, which we want to minimize.
final class	MinimizeMaximumTardiness	Implements the scheduling cost function known as maximum tardiness, which we want to minimize.
final class	WeightedEarlinessTardiness	Implements the scheduling cost function known as weighted earliness plus weighted tardiness.
final class	WeightedFlowtime	Implements the scheduling cost function known as weighted flowtime.
final class	WeightedLateness	Implements the scheduling cost function known as weighted lateness.
final class	WeightedNumberTardyJobs	Implements the scheduling cost function known as weighted number of tardy jobs, which we want to minimize.
final class	WeightedSquaredTardiness	Implements the scheduling cost function known as weighted squared tardiness.
final class	WeightedTardiness	Implements the scheduling cost function known as weighted tardiness.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.problems.tsp

Classes in org.cicirello.search.problems.tsp that implement IntegerCostOptimizationProblem

Modifier and Type	Class	Description
static final class	RandomTSPMatrix.Integer	This class implements the Traveling Salesperson Problem (TSP), and its variant, the Asymmetric Traveling Salesperson Problem (ATSP), by generating a random distance matrix, with integer cost edges.
static final class	TSP.Integer	Cost function for the Traveling Salesperson Problem (TSP), where edge costs are integer valued.
static final class	TSP.IntegerMatrix	Cost function for the Traveling Salesperson Problem (TSP), where edge costs are integer valued, and where all edge costs between pairs of cities are precomputed.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.sa

Constructors in org.cicirello.search.sa with parameters of type IntegerCostOptimizationProblem

Modifier	Constructor	Description
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems, with a default annealing schedule of SelfTuningLam, which is the Self-Tuning Lam annealing schedule of Cicirello (2021).
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, ProgressTracker<T> tracker)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems, with a default annealing schedule of SelfTuningLam, which is the Self-Tuning Lam annealing schedule of Cicirello (2021).
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, ProgressTracker<T> tracker, SimpleLocalMetaheuristic<T> hc)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems, with a default annealing schedule of SelfTuningLam, which is the Self-Tuning Lam annealing schedule of Cicirello (2021), and which runs a hill climber as a post-processing step.
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems.
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, ProgressTracker<T> tracker)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems.
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, ProgressTracker<T> tracker, SimpleLocalMetaheuristic<T> hc)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems that runs a hill climber as a post-processing step.
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, AnnealingSchedule anneal, SimpleLocalMetaheuristic<T> hc)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems that runs a hill climber as a post-processing step.
	SimulatedAnnealing(IntegerCostOptimizationProblem<T> problem, UndoableMutationOperator<T> mutation, Initializer<T> initializer, SimpleLocalMetaheuristic<T> hc)	Creates a SimulatedAnnealing search instance for integer-valued optimization problems, with a default annealing schedule of SelfTuningLam, which is the Self-Tuning Lam annealing schedule of Cicirello (2021), and which runs a hill climber as a post-processing step.

Uses of IntegerCostOptimizationProblem in org.cicirello.search.ss

Constructors in org.cicirello.search.ss with parameters of type IntegerCostOptimizationProblem

Modifier	Constructor	Description
	IterativeSampling(IntegerCostOptimizationProblem<T> problem, Initializer<T> initializer)	Constructs an iterative sampling search for a integer-valued optimization problem.
	IterativeSampling(IntegerCostOptimizationProblem<T> problem, Initializer<T> initializer, ProgressTracker<T> tracker)	Constructs an iterative sampling search for a integer-valued optimization problem.