Package org.cicirello.search.problems.scheduling

Class WeightedCriticalRatio

java.lang.Object

org.cicirello.search.problems.scheduling.WeightedShortestProcessingTime

org.cicirello.search.problems.scheduling.WeightedCriticalRatio

All Implemented Interfaces:

ConstructiveHeuristic<Permutation>

public final class WeightedCriticalRatio
extends WeightedShortestProcessingTime

This is an implementation of a variation of the weighted critical ratio heuristic. The usual definition of this heuristic is: h(j) = (w[j]/p[j])(1/(1+S(j)/p[j])), where w[j] is the weight of job j, p[j] is its processing time, and S(j) is a calculation of the slack of job j where slack S(j) is d[j] - T - p[j] - s[j]. The d[j] is the job's due date, T is the current time, and s[j] is any setup time of the job (for problems with setup times).

Historically, this heuristic has been criticized for allowing negative evaluations (i.e., slack S(j) is negative for jobs completing late). Additionally, this library's use of constructive heuristics is for stochastic sampling, for which we require positive heuristic values. Therefore, we have altered the definition as follows: h(j) = (w[j]/p[j])(1/(1+max(0,S(j))/p[j])).

Furthermore, the constant MIN_H defines the minimum value the heuristic will return, preventing h(j)=0 in support of stochastic sampling algorithms for which h(j)=0 is problematic. This implementation returns max( MIN_H, h(j)), where MIN_H is a small non-zero value.

Field Summary

Fields

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

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method	Description
int	completeLength()	Gets the required length of complete solutions to the problem instance for which this constructive heuristic is configured.
IncrementalEvaluation<Permutation>	createIncrementalEvaluation()	Creates an IncrementalEvaluation object corresponding to an initially empty Partial for use in incrementally constructing a solution to the problem for which this heuristic is designed.
Partial<Permutation>	createPartial(int n)	Creates an empty Partial solution, which will be incrementally transformed into a complete solution of a specified length.
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

Field Detail

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 Detail

WeightedCriticalRatio

public WeightedCriticalRatio(SingleMachineSchedulingProblem problem)

Constructs an WeightedCriticalRatio heuristic.

Parameters:

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

Throws:

IllegalArgumentException - if problem.hasDueDates() returns false.

Method Detail

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.

Specified by:

h in interface ConstructiveHeuristic<Permutation>

Overrides:

h in class WeightedShortestProcessingTime

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.

createIncrementalEvaluation

public IncrementalEvaluation<Permutation> createIncrementalEvaluation()

Description copied from interface: ConstructiveHeuristic

Creates an IncrementalEvaluation object corresponding to an initially empty Partial for use in incrementally constructing a solution to the problem for which this heuristic is designed. The object returned incrementally computes any data associated with a Partial as needed by the ConstructiveHeuristic.h(org.cicirello.search.ss.Partial<T>, int, org.cicirello.search.ss.IncrementalEvaluation<T>) method. The ConstructiveHeuristic.h(org.cicirello.search.ss.Partial<T>, int, org.cicirello.search.ss.IncrementalEvaluation<T>) method will assume that it will be given an object of the specific runtime type returned by this method. It is unsafe to pass IncrementalEvaluation objects created by one heuristic to the ConstructiveHeuristic.h(org.cicirello.search.ss.Partial<T>, int, org.cicirello.search.ss.IncrementalEvaluation<T>) method of another.

The default implementation simply returns null, which is appropriate for heuristics that won't benefit from incrementally computing heuristic information.

Returns:

An IncrementalEvaluation for an empty Partial to be used for incrementally computing any data required by the ConstructiveHeuristic.h(org.cicirello.search.ss.Partial<T>, int, org.cicirello.search.ss.IncrementalEvaluation<T>) method.

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