Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling

271 Pages·2016·4.39 MB·English

by  Ghaith Rabadi (eds.)

International Series in
Operations Research & Management Science
Ghaith Rabadi E ditor
Heuristics,
Metaheuristics and
Approximate Methods
in Planning and
Scheduling
International Series in Operations Research
& Management Science
Volume236
SeriesEditor
CamilleC.Price
StephenF.AustinStateUniversity,TX,USA
AssociateSeriesEditor
JoeZhu
WorcesterPolytechnicInstitute,MA,USA
FoundingSeriesEditor
FrederickS.Hillier
StanfordUniversity,CA,USA
Moreinformationaboutthisseriesathttp://www.springer.com/series/6161

Ghaith Rabadi
Editor
Heuristics, Metaheuristics
and Approximate Methods
in Planning and Scheduling
123
Editor
GhaithRabadi
EngineeringManagement
andSystemsEngineering
OldDominionUniversity
Norfolk,VA,USA
ISSN0884-8289 ISSN2214-7934 (electronic)
InternationalSeriesinOperationsResearch&ManagementScience
ISBN978-3-319-26022-8 ISBN978-3-319-26024-2 (eBook)
DOI10.1007/978-3-319-26024-2
LibraryofCongressControlNumber:2015954630
SpringerChamHeidelbergNewYorkDordrechtLondon
©SpringerInternationalPublishingSwitzerland2016
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To themostimportantwomen in mylife:
Shereen, Celine, Renee, Karoline,and Lana.

Introduction
Planning and scheduling research has started at the early years of Operation
Research (OR) more than 50 years ago. Since then, people have been motivated
and challenged by the complexity of planning and scheduling problems. Most of
theresearchinthisfieldis commonlypublishedin varioustheoreticalandapplied
ORjournals,whicharealsohometomanyotherORtopics.Traditionally,planning
andschedulingproblemsareaclassofdiscreteoptimizationproblems,whichhave
mostlybeenaddressedbylinearandnonlinearmathematicalprogrammingmodels.
Despite all the progress achieved in mathematical programming methods and the
advancement in the computer technology, the vast majority of practical planning
and scheduling problems are NP-complete/NP-hard which are time-consumingto
solveviamathematicalprogrammingduetotheircomputationallyexplosivenature.
Hence,thedevelopmentininexactmethodsandheuristicshasbeeninstrumentalto
solvingsuchproblemsespeciallyforlargeinstances.
Thescopeofthisbookislimitedtoheuristics,metaheuristics,andapproximate
methodsas applied to planningand schedulingproblems. While it is notpossible
to give a comprehensivetreatment of this topic in one book,the aim of this work
istoprovidethereaderwithadiversesetofplanningandschedulingproblemsand
differentheuristic approachesto solve them. The problemsrange from traditional
single stage and parallel machine problems to more modern settings such as
robotic cells and flexible job shop networks. Furthermore, some chapters deal
with deterministic problems, while some others treat stochastic problems. Unlike
most of the literature that deals with planning and scheduling problems in the
manufacturing and production environments, in this book the environments were
extendedtonontraditionalapplicationssuchasspatialscheduling(optimizingspace
overtime),runwayscheduling,andsurgicalscheduling.Thesolutionmethodsused
in the different chapters of the book also spread from well-established heuristics
and metaheuristics such as Genetic Algorithms, Simulated Annealing, and Tabu
Search to more recent ones such as Ant Colony Optimization, Meta-RaPS, and
WormOptimization.
vii
viii Introduction
None of the chapters has been previously published in its totality and each
chapter offers a contribution to the body of the knowledge by presenting results
and insights from applying heuristics, metaheuristics, or approximate methods to
complex,recent,anddiverseproblems.
Norfolk,VA,USA GhaithRabadi
Contents
1 ApproximationAlgorithmsforSpatialScheduling..................... 1
ChristopherGarciaandGhaithRabadi
2 Estimating the Costs of Planned Changes Implied
byFreezingProductionPlans............................................. 17
Po-ChenLinandRehaUzsoy
3 StochasticSchedulingforaNetworkofFlexibleJobShops........... 45
SubhashC.Sarin,HanifD.Sherali,AmrushaVaradarajan,
andLingruiLiao
4 AFree-Slack-BasedGeneticAlgorithmfortheRobotic
CellProblemwithControllableProcessingTimes...................... 77
MohammedAl-Salem, Mohamed Haouari, Mohamed
Kharbeche,andWaelKhallouli
5 Metaheuristic for Randomized Priority Search
(Meta-RaPS):ATutorial................................................... 95
ReinaldoJ.Moraga
6 Performance of an Intensification Strategy Based
onLearninginaMetaheuristic:Meta-RaPSwithPathRelinking.... 109
ArifArinandGhaithRabadi
7 Meta-RaPSforaBi-objectiveUnrelatedParallelMachine
SchedulingProblem........................................................ 127
NixonDcouthoandReinaldoMoraga
8 HeuristicsandMeta-heuristicsforRunwaySchedulingProblems ... 141
FarbodFarhadi
9 A Tabu SearchAlgorithmfor the Multiple Runway
AircraftSchedulingProblem.............................................. 165
BulentSoykanandGhaithRabadi
ix