Uses of Package
org.cicirello.search.ss

Packages that use org.cicirello.search.ss

Package	Description
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.ss	This package includes classes and interfaces directly related to implementing stochastic sampling algorithms.

Classes in org.cicirello.search.ss used by org.cicirello.search.problems.scheduling

Class	Description
ConstructiveHeuristic	Classes implementing this interface are used as constructive heuristics for constructing heuristic solutions to optimization problems, as well as for certain stochastic sampling search algorithms.
IncrementalEvaluation	The implementations of constructive heuristics and stochastic samplers biased by constructive heuristics in the library support incremental updates, as the solution is heuristically assembled, to problem and/or heuristic data utilized by the heuristic.
Partial	A Partial represents a partial solution to a problem (e.g., a partial permutation or a partial integer vector) that is being iteratively constructed as a solution to an optimization problem.

Classes in org.cicirello.search.ss used by org.cicirello.search.problems.tsp

Class	Description
ConstructiveHeuristic	Classes implementing this interface are used as constructive heuristics for constructing heuristic solutions to optimization problems, as well as for certain stochastic sampling search algorithms.
IncrementalEvaluation	The implementations of constructive heuristics and stochastic samplers biased by constructive heuristics in the library support incremental updates, as the solution is heuristically assembled, to problem and/or heuristic data utilized by the heuristic.
Partial	A Partial represents a partial solution to a problem (e.g., a partial permutation or a partial integer vector) that is being iteratively constructed as a solution to an optimization problem.

Classes in org.cicirello.search.ss used by org.cicirello.search.ss

Class	Description
AcceptanceBandSampling	The AcceptanceBandSampling class implements a form of stochastic sampling search that uses a constructive heuristic to guide the random decisions.
ConstructiveHeuristic	Classes implementing this interface are used as constructive heuristics for constructing heuristic solutions to optimization problems, as well as for certain stochastic sampling search algorithms.
HeuristicBiasedStochasticSampling	Heuristic Biased Stochastic Sampling (HBSS) is a form of stochastic sampling search that uses a constructive heuristic to bias the random decisions.
HeuristicBiasedStochasticSampling.BiasFunction	Implement this interface to implement the bias function used by HBSS.
HeuristicPermutationGenerator	This class generates solutions to permutation optimization problems using a constructive heuristic.
HeuristicSolutionGenerator	This class generates solutions to optimization problems using a constructive heuristic.
HybridConstructiveHeuristic	A HybridConstructiveHeuristic maintains a list of ConstructiveHeuristic objects for a problem, for use in a multiheuristic stochastic sampling search, where each full iteration of the stochastic sampler uses a single heuristic for all decisions, but where a different heuristic is chosen for each iteration.
IncrementalEvaluation	The implementations of constructive heuristics and stochastic samplers biased by constructive heuristics in the library support incremental updates, as the solution is heuristically assembled, to problem and/or heuristic data utilized by the heuristic.
IterativeSampling	Iterative sampling is the simplest possible form of a stochastic sampling search.
Partial	A Partial represents a partial solution to a problem (e.g., a partial permutation or a partial integer vector) that is being iteratively constructed as a solution to an optimization problem.
ValueBiasedStochasticSampling	Value Biased Stochastic Sampling (VBSS) is a form of stochastic sampling search that uses a constructive heuristic to bias the random decisions.
ValueBiasedStochasticSampling.BiasFunction	Implement this interface to implement the bias function used by VBSS.