Module org.cicirello.chips_n_salsa
Class DynamicATCS
java.lang.Object
org.cicirello.search.problems.scheduling.WeightedShortestProcessingTime
org.cicirello.search.problems.scheduling.DynamicATCS
- All Implemented Interfaces:
Splittable<ConstructiveHeuristic<Permutation>>
,ConstructiveHeuristic<Permutation>
DynamicATCS is an implementation of a variation of the ATCS (Apparent Tardiness Cost with Setups)
heuristic, which dynamically updates the average processing and setup times as it constructs the
schedule. For an implementation of the original version of ATCS, without the dynamic parameter
updates, see the
ATCS
class. ATCS is defined as: h(j) = (w[j]/p[j]) exp( -max(0,d[j] - T
- p[j]) / (k1 p̄) ) exp( -s[i][j] / (k2 s̄)), where w[j] is the
weight of job j, p[j] is its processing time, d[j] is the job's due date, T is the current time,
and s[i][j] is any setup time of the job if it follows job i. The k1 and k2
are parameters that can be tuned based on problem instance characteristics, p̄ is the
average processing time of remaining unscheduled jobs, and s̄ is the average setup time of
the remaining unscheduled jobs. The authors of the ATCS heuristic simply computed p̄ and
s̄ once at the start, while our implementation updates these dynamically along the way as
jobs are scheduled.
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.
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Field Summary
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Constructor Summary
ConstructorDescriptionConstructs an DynamicATCS heuristic.DynamicATCS
(SingleMachineSchedulingProblem problem, double k1, double k2) Constructs an DynamicATCS heuristic. -
Method Summary
Modifier and TypeMethodDescriptionfinal int
Gets the required length of complete solutions to the problem instance for which this constructive heuristic is configured.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.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>
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
split
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Field Details
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MIN_H
public static final double MIN_HThe 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:
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Constructor Details
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DynamicATCS
Constructs an DynamicATCS heuristic.- Parameters:
problem
- The instance of a scheduling problem that is the target of the heuristic.k1
- A parameter to the heuristic, which must be positive.k2
- A parameter to the heuristic, which must be positive.- Throws:
IllegalArgumentException
- if problem.hasDueDates() returns false.IllegalArgumentException
- if k ≤ 0.0.
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DynamicATCS
Constructs an DynamicATCS heuristic. Sets the values of k1 and k2 according to the procedure described by the authors of the ATCS heuristic.- Parameters:
problem
- The instance of a scheduling problem that is the target of the heuristic.- Throws:
IllegalArgumentException
- if problem.hasDueDates() returns false.
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Method Details
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h
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 interfaceConstructiveHeuristic<Permutation>
- Overrides:
h
in classWeightedShortestProcessingTime
- Parameters:
p
- The current state of the Partialelement
- The element under consideration for adding to the PartialincEval
- An IncrementalEvaluation of p. This method assumes that incEval is of the same runtime type as the object returned byConstructiveHeuristic.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.
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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 theConstructiveHeuristic.h(org.cicirello.search.ss.Partial<T>, int, org.cicirello.search.ss.IncrementalEvaluation<T>)
method. TheConstructiveHeuristic.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 theConstructiveHeuristic.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.
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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 interfaceConstructiveHeuristic<Permutation>
- Returns:
- the instance of the optimization problem that is the subject of this heuristic.
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createPartial
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 interfaceConstructiveHeuristic<Permutation>
- Parameters:
n
- the desired length of the final complete solution.- Returns:
- an empty Partial solution
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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 interfaceConstructiveHeuristic<Permutation>
- Returns:
- length of solutions to the problem instance for which this heuristic is configured
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