Module org.cicirello.chips_n_salsa

Package org.cicirello.search.problems.scheduling

Class SmallestNormalizedSetup

java.lang.Object

org.cicirello.search.problems.scheduling.SmallestNormalizedSetup

All Implemented Interfaces:

Splittable<ConstructiveHeuristic<Permutation>>, ConstructiveHeuristic<Permutation>

public final class SmallestNormalizedSetup
extends Object

This heuristic is smallest normalized setup. The normalized setup of job j is: s[i][j] / ave_k(s[k][j]), where s[i][j] is the setup time for job j if it follows job i, job i is the most recently scheduled job, and ave_k(s[k][j]) is the average setup for job j, averaged over the possible remaining predecessors. We define the smallest normalized setup heuristic as: h(j) = 1 / (1 + s[i][j]/ave_k(s[k][j])).

Field Summary

Fields

Modifier and Type	Field	Description
static final double	MIN_H	The minimum heuristic value.

Constructor Summary

Constructors

Constructor	Description
SmallestNormalizedSetup(SingleMachineSchedulingProblem problem)	Constructs an SmallestNormalizedSetup heuristic.

Method Summary

Modifier and Type	Method	Description
final int	completeLength()	Gets the required length of complete solutions to the problem instance for which this constructive heuristic is configured.
final Partial<Permutation>	createPartial(int n)	Creates an empty Partial solution, which will be incrementally transformed into a complete solution of a specified length.
final Problem<Permutation>	getProblem()	Gets a reference to the instance of the optimization problem that is the subject of this heuristic.
double	h(Partial<Permutation> p, int element, IncrementalEvaluation<Permutation> incEval)	Heuristically evaluates the possible addition of an element to the end of a Partial.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.cicirello.search.ss.ConstructiveHeuristic

createIncrementalEvaluation, split

Field Details

MIN_H

public static final double MIN_H

The minimum heuristic value. If the heuristic value as calculated is lower than MIN_H, then MIN_H is used as the heuristic value. The reason is related to the primary purpose of the constructive heuristics in the library: heuristic guidance for stochastic sampling algorithms, which assume positive heuristic values (e.g., an h of 0 would be problematic).

See Also:

• Constant Field Values

Constructor Details

SmallestNormalizedSetup

public SmallestNormalizedSetup(SingleMachineSchedulingProblem problem)

Constructs an SmallestNormalizedSetup heuristic.

Parameters:

problem - The instance of a scheduling problem that is the target of the heuristic.

Method Details

h

public double h(Partial<Permutation> p,
 int element,
 IncrementalEvaluation<Permutation> incEval)

Description copied from interface: ConstructiveHeuristic

Heuristically evaluates the possible addition of an element to the end of a Partial. Higher evaluations imply that the element is a better choice for the next element to add. For example, if you evaluate two elements, x and y, with h, and h returns a higher value for y than for x, then this means that y is believed to be the better choice according to the heuristic. Implementations of this interface must ensure that h always returns a positive result. This is because stochastic sampling algorithms such as HBSS and VBSS assume that the constructive heuristic returns only positive values.

Parameters:

p - The current state of the Partial

element - The element under consideration for adding to the Partial

incEval - An IncrementalEvaluation of p. This method assumes that incEval is of the same runtime type as the object returned by ConstructiveHeuristic.createIncrementalEvaluation().

Returns:

The heuristic evaluation of the hypothetical addition of element to the end of p. The higher the evaluation, the more important the heuristic believes that element should be added next. The intention is to compare the value returned with the heuristic evaluations of other elements. Individual results in isolation are not necessarily meaningful.

getProblem

public final Problem<Permutation> getProblem()

Description copied from interface: ConstructiveHeuristic

Gets a reference to the instance of the optimization problem that is the subject of this heuristic.

Specified by:

getProblem in interface ConstructiveHeuristic<Permutation>

Returns:

the instance of the optimization problem that is the subject of this heuristic.

createPartial

public final Partial<Permutation> createPartial(int n)

Description copied from interface: ConstructiveHeuristic

Creates an empty Partial solution, which will be incrementally transformed into a complete solution of a specified length.

Specified by:

createPartial in interface ConstructiveHeuristic<Permutation>

Parameters:

n - the desired length of the final complete solution.

Returns:

an empty Partial solution

completeLength

public final int completeLength()

Description copied from interface: ConstructiveHeuristic

Gets the required length of complete solutions to the problem instance for which this constructive heuristic is configured.

Specified by:

completeLength in interface ConstructiveHeuristic<Permutation>

Returns:

length of solutions to the problem instance for which this heuristic is configured