Uses of Package
org.cicirello.search.ss
Package
Description
Package of classes and interfaces related to representing and solving scheduling problems, which
includes implementations of constructive heuristics for scheduling problems.
Classes and interfaces related to the Traveling Salesperson Problem (TSP).
This package includes classes and interfaces directly related to implementing stochastic sampling
algorithms.

ClassDescriptionClasses implementing this interface are used as constructive heuristics for constructing heuristic solutions to optimization problems, as well as for certain stochastic sampling search algorithms.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.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.

ClassDescriptionClasses implementing this interface are used as constructive heuristics for constructing heuristic solutions to optimization problems, as well as for certain stochastic sampling search algorithms.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.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.

ClassDescriptionThe AcceptanceBandSampling class implements a form of stochastic sampling search that uses a constructive heuristic to guide the random decisions.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.Heuristic Biased Stochastic Sampling (HBSS) is a form of stochastic sampling search that uses a constructive heuristic to bias the random decisions.Implement this interface to implement the bias function used by HBSS.This class generates solutions to permutation optimization problems using a constructive heuristic.This class generates solutions to optimization problems using a constructive heuristic.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.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.Iterative sampling is the simplest possible form of a stochastic sampling search.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.Value Biased Stochastic Sampling (VBSS) is a form of stochastic sampling search that uses a constructive heuristic to bias the random decisions.Implement this interface to implement the bias function used by VBSS.