Program - Alex Grasas

351 Pages·2010·2.17 MB·English

T S
ECHNICAL ESSIONS
Monday, 9:00-10:20 We consider the NP-hard Steiner tree problem under a two-stage stochastic
modelwithrecourseandfinitelymanyscenarios.Wediscussundirected,semi-
directed, and directed cut-set based integer programming models, and sug-
(cid:4) gestabranch-and-cutapproachbasedonBendersdecompositionandaderived
MA-01
Integer-L-shapedalgorithm. Wecompareourdifferentmodelsboththeoreti-
Monday,9:00-10:20 cally,namelyfromapolyhedralpointofview,andcomputationally.
AulaMagna
3- ExactandHeuristicAlgorithmsfortheBoundedCycle
Keynote Talk 1 CoverProblem
Stream: KeynoteSpeakers IreneLoiseau,DepartamentodeComputación-,Facultadde
CienciasExactasyNaturales,UniversidaddeBuenosAires,
Invitedsession
PabellónI-CiudadUniversitaria,1428,BuenosAires,
Chair:Gerhard-WilhelmWeber,InstituteofAppliedMathematics, Argentina,[email protected]
MiddleEastTechnicalUniversity,ODTÜ,06531,Ankara,Turkey,
[email protected] WewillpresentanewexactalgorithmandheuristicsfortheBoundedCycle
CoverProblem. BCCPrequirestodetermineaminimumcostcyclecoverof
agraph,withcyclesboundedinlengthandnumberofedges. Thisproblem
1- Safetractableapproximationsofchanceconstraints
arisesinseveralsituationsrelatedtotelecommunicationsnetworksdesign,as,
forexample,whenwewanttodesignfiber-optictelecommunicationsnetworks
ArkadiNemirovski,SchoolofIndustrialandSystems
thatemploymultipleself-healingringstoprovideroutingforcommunication
Engineering,GeorgiaInstituteofTechnology,765FerstDrive,
traffic,evenintheeventofafibercutorotherkindsoffailures.
NW,GA30332-0205,Atlanta,Germany,
[email protected]
4- Reverse Multistar Inequalities and Vehicle Routing
Whenoptimizingunderstochasticuncertainty,theentityofprimaryimportance Problemswithlowerboundcapacities
isachanceconstraintProbqsi->P f(x;qsi)inQ >=1-epsilon,forallPinPP
wherexisthedecisionvector,qsiisarandomperturbationwithdistributionP LuisGouveia,DEIO,UniversityofLisbon,CampoGrande,
knowntobelongtoagivenfamilyPP,Qisagiventargetset,andepsilon«1 BlocoC6,1749-016,Lisbon,Portugal,[email protected],Juan
isagiventolerance.Asideofahandfulofspecialcases,chanceconstrainsare JoséSalazarGonzález
computationallyintractable:first,itisdifficulttocheckefficientlywhetherthe
In this talk we discuss, present and test models for the Capacitated Vehicle
constraintissatisfiedatagivenx,andsecond,thefeasiblesetofachancecon-
RoutingProblemwitharclowerbounds. Weintroducetheso-calledreversed
strainttypicallyisnonconvex,whichmakesitproblematictooptimizeunder
multistarinequalitiesandtwootherrelatedfamiliesofinequalities,andshow
theconstraint. Giventhesedifficulties,anaturalwaytoprocessachancecon-
thattheyarerelevantformodellingthisroutingproblem. Wepresentresults
straintistoreplaceitwithitssafetractableapproximationatractableconvex
fromabranch-and-cutalgorithmwhichusesthenewinequalitiesforsolving
constraintwiththefeasiblesetcontainedintheoneofthechanceconstraint.
instanceswithupto50customers.
Inthetalk,weoverviewsomerecentresultsinthisdirection,withemphasison
chanceversionsofwell-structuredconvexconstraints(primarily,affinelyper-
turbedscalarlinearandlinearmatrixinequalities)andestablishlinksbetween
thistopicandRobustOptimization. (cid:4)
MA-03
Monday,9:00-10:20
(cid:4) MA-02 3.2.15
Monday,9:00-10:20 TSP
3.2.14 Stream: Metaheuristics
Combinatorial Optimization I Invitedsession
Chair:JoséA.Moreno-Pérez,Estadística,I.O.yComputación,
Stream: CombinatorialOptimization
UniversityofLaLaguna,LaLaguna,Spain,[email protected]
Invitedsession
Chair:NorainiMohdRazali,Mechanical&Manufacturing
Chair:IvanaLjubic,DepartmentofStatisticsandDecisionSupport Engineering,DublinCityUniversity,Dublin9,Dublin,Ireland,
Systems,UniversityofVienna,Bruennerstr.72,1210,Vienna, [email protected]
Austria,[email protected]
1- An algorithm for solving the traveling salesman prob-
1- Spanning Trees with Node Degree Dependent Costs lem (tsp) based on multimodal transport, using a se-
andKnapsackReformulations cuenceoflinearproblems(lp)
PedroMoura,DEIO,UniversityofLisbon,CampoGrande, LuisMoreno,Systems,UniversidadNacionaldeColombia,
BlocoC6,1749-016,Lisbon,Portugal,[email protected],Luis FacultaddeMinascra.8065-223,BloqueM8oficina207,1,
Gouveia Medellin,Antioquia,Colombia,[email protected],Javier
TheDegreeconstrainedMinimumSpanningTreeProblem(DMSTP)consists Diaz,GloriaPena
infindingaminimalcostspanningtreesatisfyingtheconditionthateverynode
Ahybridalgorithmisproposedbasedonheuristicsandlinearprogramming.A
hasdegreenogreaterthanafixedvalue. Weconsiderageneralizationofthe
relaxedlinearproblem(LP)issolved.Ifthesolutionhasseveralnonconnected
DMSTPwithamoregeneralobjectivefunctionincludingmodularcostsasso-
circuitsanewheuristicLPisusedtoconnectthecircuits,assumingthecities
ciatedtothedegreeofeachnode, whichhaveatechnologicalmotivationin
ineachcircuitintherelaxedsolutionareclosebetweenthem.Thecircuitsare
thecontextoftelecommunicationsnetworks. WepresentLPmodelstogether
connectedaswoulddosomebodyaftervisitingbycarseveralcitiesinaregion
withsomevalidinequalitiesandcomparetheirrespectivelinearprogramming
thattakesaplanetovisitoptimallyanothersetofregionswithadditionalcities.
relaxationsusingcableandwirelessnetworkbasedinstances.
Ifwhenconnectingthecircuitofcircuitsthereareagainseveralnonconnected
circuitstheheuristicLPissolvedinaniterativewaythatdecreasesthelinear
2- SolvingtheStochasticSteinerTreeProblembyBranch- problemsizeuntilallthecitiesbecomeshortlyandeasilyconnected.
and-Cut
2- AModifiedElectromagnetism-likeAlgorithmforTravel-
BerndZey,TUDortmund,FrankfurterWeg3,59439,
lingSalesmanProblemswithPrecedenceConstraints
Holzwickede,Germany,[email protected],Immanuel
Bomze,MarkusChimani,MichaelJuenger,IvanaLjubic,Petra AlkinYurtkuran,IndustrialEngineeringDepartment,Uludag
Mutzel University,UludagUniversity,IndustrialEngineering
1
MA-04 EURO24-Lisbon2010
WedevelopaTabuSearch(TS)algorithmwithaprobabilisticlocalsearchafter
Department,16059,Bursa,Turkey,[email protected],Erdal
eachiterationtosolvetheorderacceptanceandschedulingproblemonasingle
Emel
machinewithsequencedependentsetuptimes. Wecomparetheperformance
TravelingSalesmanProblemwithPrecedenceConstraints(TSPPC)isanim- oftheTSalgorithmtoagreedyconstructiveheuristicfromtheliterature,using
portantvariantofTravelingSalesmanProblem.TSPPCbelongstotheclassof upperboundsbasedonamixedintegerprogrammingformulation. Computa-
NP-Hardproblemswherethereexitsaprecedencerelationshipbetweencus- tionalstudiesshowthattheTSalgorithmgivessignificantlybettersolutions
tomers. Inthisstudy,aModifiedElectromagnetism-likeAlgorithm(EMA)is thanthoseoftheconstructiveheuristicintermsofobjectivefunctionvaluein
appliedtosolveTSPPCproblems.Thekeyconceptoftheproposedalgorithm allinstancestestedwithasmallincreaseinruntime.
istheprojectionoftheparticlespaceontoanewcoordinatespacewhereeach
precedenceconstraintisensured. ThecomputationalresultsshowthatModi-
3- Approximate methods for solving the operating room
fiedEMAgivespromisingresultswithinacceptablecomputationaltimes.
planningproblem
3- Performance comparison between different GA selec-
tionstrategiesinsolvingTSPinstance. JoseM.Molina-Pariente,UniversityofSeville,Spain,
[email protected],JoseMFraminan,PazPerezGonzalez
NorainiMohdRazali,Mechanical&Manufacturing
Engineering,DublinCityUniversity,Dublin9,Dublin,Ireland, Inthiscommunication,weaddresstheoperatingroomplanningproblemfora
[email protected],JohnGeraghty surgeryunit. Thisprobleminvolvesdeterminingasurgeryschedulethatspec-
ifiesthenumberofsurgicalcasestobescheduledinagivenplanninghorizon
Thisstudypresentsthecomparisonofgeneticalgorithmperformanceonsolv-
togetherwiththedateoftheinterventionandthespecificoperatingroomin
ingTSPusingtwodifferentstochasticselectionmethodswhicharetournament
whicheachsurgicalcasewillbeperformed.Tosolvethisproblem,wepresent
androulettewheel. TheGAismainlycomposedofthreegeneticoperations
newconstructiveheuristicsandalocalsearchmethod. Weevaluatetheper-
which are selection, crossover and mutation. With the same crossover and
formanceofthesemethodsbygeneratingalargesetofinstancesbasedonan
mutation operation, the studyis focussedon comparing theeffect of differ-
analysisoftheliterature.
entselectionstrategytotheperformanceofconvergencethatgivesoptimum
solution.NumericalexperimentsshowthatGAwithtournamentselectioncon-
vergesmuchfasterthanroulettewheelselection. 4- A GRASP approach to the Multi-Task Employee
TimetablingProblem
4- A Data Mining Based Heuristic Approach for Solution
ofTravellingSalesmanProblem PilarTormos,STATISTICSANDOPERATIONSRESEARCH,
HandeGulkac,ComputerEngineering,OkanUniversity,Turkey, UNIVERSIDADPOLITECNICADEVALENCIA,CAMINO
[email protected],SemiyeGönülol,AhmetCihan, DEVERAS/N,VALENCIA,46022,VALENCIA,SPAIN,
HalenurS¸ahin,AlpaslanFiglali Spain,[email protected],AntonioLova
Travelling Salesman Problem (TSP) is a well known NP-hard optimization EmployeeTimetablingProblem(ETP)istheoperationofassigningemployees
problem. Manymethodsareappliedincludingheuristics,mathematicalpro- totasksinasetofshiftsduringaperiodoftimewhilesatisfyingtheexisting
grammingandmetaheuristicsforobtaininggoodsolutions.Inthisstudyadata constraintsandpreferences.Anextensionofthisproblem,theMulti-TaskEm-
miningbasedheuristicapproachisappliedforthesolutionofTSP.Procedure ployeeTimetablingProblem(MTETP)impliestheassignmentofthesequence
usesarepetitiveandforcedrandomtourgenerationapproach. Thesetofbest of tasks to be performed by each employee every working day of the plan-
randomtoursareanalyzedviadataminingtoolstoobtaintherelations.Using ninghorizonanditisespeciallyrelevantforcommercialcompanies.Agreedy
therulesderivedfromtherelations,theTSPtourisobtained. Theresultsare randomizedadaptivesearchprocedure(GRASP)isdevelopedtosolveitand
promisingwhileconsideringit’ssimplicity. embeddedinacomputer-aidedsystem(OPTIHPER).Acustomizedversionof
itisinusewithverysatisfactoryresultsbyaleadingSpanishdistributioncom-
pany.
(cid:4)
MA-04
Monday,9:00-10:20
3.2.13 (cid:4) MA-05
Scheduling with metaheuristics Monday,9:00-10:20
3.2.16
Stream: Metaheuristics
Invitedsession Theory
Chair:LionelAmodeo,CharlesDelaunayInstitute,Universityof
Stream: Metaheuristics
TechnologyofTroyes,12RueMarieCurieBP2060,10000,Troyes,
Invitedsession
France,[email protected]
Chair:GustavoMelo,ComputerScience,UniversidadeEstadualdo
Chair:FaroukYalaoui,InstitutCharlesDelaunay,ICDLOSI,
Ceará,Ruacésarfonseca410ap301bairropapicu,60176-110,
UniversityofTechnologyofTroyes,12,ruemariecurieBP2060,
Fortaleza,Ceará,Brazil,[email protected]
10000,Troyes,France,[email protected]
Chair:ZahiraBenkhellat,informatique,sciencesexactes,Bejaia
1- SingleMachineSchedulingwithRejection: Minimizing
universityQlgerie,teacher,Algeria,[email protected]
totalWeightedCompletionTimeandRejectionCost
AtefehMoghaddam,CharlesDelaunayInstitute,Universityof 1- AnalysisofsoftwarefortheNGStechnology: TheSur-
TechnologyofTroyes,12rueMarieCurie„Troyes,France, vivalGuide
10000,Troyes,France,[email protected],Farouk
Yalaoui,LionelAmodeo BrunoVieira,ComputationalBiology&PopulationGenomics
Group,CentrodeBiologiaAmbiental,Departamentode
Itisalwaysassumedthatwehavetoprocessalljobs. However,wecanbreak
theassumptionbyrejectingcertainjobs. Inthispaper, weconsiderthatthe BiologiaAnimal,FaculdadedeCiênciasdaUniversidadede
jobscanbeeitherscheduledonasinglemachineorberejectedatthecostof Lisboa,CampoGrande,1749-016,Lisbon,Portugal,
apenalty. Twoobjectivefunctionsareconsidered: minimizingtotalweighted [email protected],FranciscoPinaMartins,SofiaSeabra,
completiontimesandminimizingtotalpenalties.Weapplytwo-phasemethod OctavioPaulo
tofindallPareto-optimalsolutions. Wealsoproposebi-objectivesimulated
annealingalgorithmtofindestimatedPareto-optimalsolutions.Bycomparing NextGenerationSequencing(NGS)technologiesallowthegenerationoflarge
thesolutions,weshowthattheresultsarereasonablygood. amountsofdatainashorttimespanandforarelativelylowcost. Amulti-
tudeofsoftwarewasrecentlydevelopedtoaddressthedifficultiesgenerated
2- A Tabu Search Algorithm for Order Acceptance and byNGS,suchasassemblingthemillionsofreads,contiggenerationandthe
Scheduling followupannotation.Thecoverrateisalsorelevanttotheresultsaccuracyand
thedetectionofgeneticvariation,eitherintheformofSNPsorCNVs.Inthis
BahriyeCesaret,IndustrialEngineering,KocUniversity,Koc communicationweaddressseveralcriticalbioinformaticsstepsandcompare
University,RumelifeneriyoluSariyer,34450,Istanbul,Turkey, currentsoftwareandalgorithmstotackletheseproblems.
[email protected],CeydaOguz,SibelSalman
2
EURO24-Lisbon2010 MA-07
(cid:4) (cid:4)
MA-06 MA-07
Monday,9:00-10:20 Monday,9:00-10:20
8.2.30 8.2.47
DEA Methodology I Recent Developments in Mathematical
Programming
Stream: DEAandPerformanceMeasurement
Invitedsession Stream: MathematicalProgramming[c]
Chair:DimitrisDespotis,DepartmentofInformatics,Universityof Contributedsession
Piraeus,80,Karaoli&DimitriouStreet,18534,Piraeus,Greece, Chair:Gerhard-WilhelmWeber,InstituteofAppliedMathematics,
[email protected] MiddleEastTechnicalUniversity,ODTÜ,06531,Ankara,Turkey,
[email protected]
1- DEAapproachforevaluatingperformanceconsidering
Chair:JerzyFilar,MathematicsandStatistics,UniversityofSouth
institutiongoal Australia,MawsonLakesBlvd,5095,MawsonLakes,SA,Australia,
j.fi[email protected]
Sheu-huaChen,DistributionManegement,NationalChin-Yi
UniversityofTechnology,Taipin,Taichung,Taiwan,ROC,411, 1- A Relax-and-Fix Lagrangean Relaxation Based Algo-
Taichung,Taiwan,Taiwan,[email protected],HongTauLee
rithmforaClassofMultiple-ChoiceIntegerProblems
Inthedataenvelopmentanalysis(DEA)approachsomedecision-makingunits AbdelkaderSbihi,InformationSystemsandDecisionMaking
mayreachperformanceefficiencybytheiroutstandingperformanceonsome Science,Audencia-NantesSchoolofManagement,8routedela
relativeunimportantoutputitems. Inthisresearch,wetrytoaddthestrictly
Jonelière,BP31222,44312,NantesCedex3,France,
predefinedrelationshipsofoutputitemsintheexistedmodelthatexpressedthe
[email protected]
relativeimportanceofthoseinputoroutputitems.Accordingtothisapproach,
onlytheDMUsthatreallymatchthepredefinedrequirementsandhavegood WeproposeaLagrangeanrelaxationbased-algorithmforsomehardcombina-
performancecanberegardedasefficientunits. Thatistosaythemeaningof torialproblems. Theideaistorelaxacertaintypeofconstraintsthentofix
performancedependsonthegoalstheorganizationpursues.Thisismeaningful variablestotheiroptimalvalue. Weconsider: (i)theMultiple-ChoiceKnap-
formanagerialpractices. Acaseofperformanceevaluationoffacultyindif- sackProblem(MCKP)and(ii)theMultiple-ChoiceSubsetSumProblem(MC-
ferenttypesofuniversitywithspecificdevelopmentorientationisprovidedto SSP)whichcanbeconsideredasaspecialcaseoftheMCKP.WeusedMCSSP
illustratetheproposedidea. asanauxiliaryproblemtotightenthecapacityconstraint. Theobtainedre-
sultsshowedahighqualityofthecomputedupperbounds.Thebenchmarkhas
demonstratedahighefficiencyoftheapproach.
2- Assessing robustness in additive DEA with interval
measurements 2- AnOptimizationMethodforSolvingAssemlyLineBal-
ancingProblem
MariaGouveia,ISCAC,QuintaAgricola-Bencanta,3040-316,
Coimbra,Portugal,[email protected],LuisC.Dias,Carlos SukranSeker,IndustrialEngineeringDepartment,Yildiz
HenggelerAntunes TechnicalUniversity,BarborosStreetYildizTechnical
UniversityIndustrialEngineeringDepartment343409Besiktas,
Thisstudyaddressestheproblemoffindingtherangeofefficiencyforeach Istanbul,Turkey,[email protected],MesutÖzgürler
DecisionMakingUnit(DMU)consideringuncertaindata. Uncertaintyinthe
DMUcoefficientsineachfactor(inputoroutput)iscapturedthroughinterval Assembly line balancing or simply line balancing is the problem of assign-
coefficients(i.e. theseareuncertainbutbounded). Atwo-phaseadditiveData ingoperationstoworkstationsalonganassemblylineinsuchawaythatthe
EnvelopmentAnalysis(DEA)modelforperformanceevaluationisused,which assignmentbeoptimalinsomesense. Assigntaskstoworkstationsobserv-
isadaptedtoincludetheconceptofsuper-efficiencytoprovidearobustness ingbalancingrestrictionsoastominimizebalancedelaywhilekeepingstation
analysisoftheDMUsinfaceofuncertaininformation. workcontentforeverystationcycletime. Therehavebeenalargenumber
ofproposalsfortheoreticalandpracticalmethodsforsolvingthelinebalance
problem. Thispaperuseoneoftheoptimizationsolutionapproachtosolve
3- A proposition of the minimum distance model in Net- assemblylinebalancingproblem.
workDEA
3- Geo-spatial data mining by model-based clustering
TohruUeda,FacultyofScienceandTechnology,Seikei methods
University,3-3-1Kichijoji-Kitamachi,180-8633,
FranciscoFigueiredo,UNIDE,ISCTE-IUL,Lisbon,Portugal,
Musashino-Shi,Tokyo,Japan,[email protected],Hirofumi
francisco.m.fi[email protected],JoséG.Dias
Amatatsu
Mostoftheclusteringtechniquesareinadequateforgeo-spatialdataminingas
MinimizationofobjectivefunctioninSBMmodelresultsinmaximizationof theytendtoignorethatspatiallycloserareastendtobemoresimilarthanthe
slackssum.Thismaximizationcorrespondstofindingapointintheproduction others. Geo-spatialclusteringaimstofindgroupsofsimilarobjectsthatare
possibilitysetthatisthefarthestpointfromeachDecisionMakingUnittobe spatiallyclose. Weproposeaclusteringalgorithmforspatialsegmentationof
evaluated. Toovercomethisshortage,weproposedtheunifiedDEAmodel. countdataunderaregressionframework,whichcombinestheNeighborhood
Traditionallinkingconstraintswherecontinuitybetweeninputandoutputis EM(NEM)andHybridEM(HEM)algorithms. Thegeo-spatialdatamining
keptmaybetooseveretoevaluateefficiencies.Consideringlinkingconstraints approachisillustratedwithgeoreferencedpoliticaldata.
andtheunifiedDEAmodelwithminimumdistance,weproposeanewnetwork
DEAmodelanddiscussefficienciesofprefecturesinJapan. 4- Alternating Proximal Algorithms and Hierarchical Se-
lectionofOptimainGames,ControlandPDE’s
4- Animprovingapproachforestimatingreturntoscalein JuanPeypouquet,Mathematics,UniversidadTecnicaFederico
DEA SantaMaria,AvEspana1680,2340000,Valparaiso,Valparaiso,
Chile,[email protected],HedyAttouch,Marco
MaryamAllahyar,mathematics,scienceandresearchbranch
Czarnecki
islamicazaduniversity,tehran-ashrafiesfahanihighway-to
Westudyalternatinganddiagonalproximalalgorithmscombiningresolvent
hesarak,0098,tehran,tehran,Iran,IslamicRepublicOf,
iterationsandapenalizationscheme. Theresultingsequenceofiteratesand,
[email protected],MohsenRostamy-malkhalifeh
underlessrestrictiveconditions,theiraveragesconvergeweaklytoapointwith
specialproperties.Wealsoanalizeasplittingmethodforstructuredvariational
In this article a new method will be suggested for the determination of the
problemsandcommentontherobustnessofthesemethods.Theresultsenable
rightandleftreturntoscale(RTS).Thenewapproachisdifferentformthatof
ustosolveconstrainedorbileveloptimizationproblems. Thismethodisap-
GolanyandYu(1997)anddoesn’thaveitsshortcomings.Ourapproachisable
pliedtobestresponsedynamicswithcosttochange,optimalcontrolproblems
toevaluatetherightandleftRTSinallconditionsforanyunit.
anddomaindecompositionforPDE’s.
3
MA-08 EURO24-Lisbon2010
(cid:4) (cid:4)
MA-08 MA-09
Monday,9:00-10:20 Monday,9:00-10:20
6.1.36 6.2.53
Project Management Software and Challenges of Mathematical Programming
Applications by Modern Applications
Stream: ProjectManagementandScheduling Stream: MathematicalProgramming
Invitedsession Invitedsession
Chair:NorbertTrautmann,DepartmentofBusinessAdministration, Chair:ZuzanaOplatkova,Dept.ofAppliedInformatics,TomasBata
UniversityofBern,IFM,APQuantitativeMethoden, UniversityinZlin,NadStranemi4511,76005,Zlin,CzechRepublic,
Schützenmattstrasse14,3012,Bern,BE,Switzerland, [email protected]
[email protected] Chair:Gerhard-WilhelmWeber,InstituteofAppliedMathematics,
Chair:ChristophSchwindt,InstituteofManagementandEconomics, MiddleEastTechnicalUniversity,ODTÜ,06531,Ankara,Turkey,
ClausthalUniversityofTechnology,Julius-Albert-Str.2,38678, [email protected]
Clausthal-Zellerfeld,Germany,[email protected]
1- An optimization approach for prediction of microbial
1- HeuristicimprovementofMicrosoftProject’sresource- growthstrategies
allocationcapabilities
PinarOzturk,SystemsBioinformatics,VrijeUniversity,
NorbertTrautmann,DepartmentofBusinessAdministration, Amsterdam,DeBoelelaan1085,1081HV,Amsterdam,
UniversityofBern,IFM,APQuantitativeMethoden, Netherlands,[email protected],DouweMolenaar
Schützenmattstrasse14,3012,Bern,BE,Switzerland,
In limited nutrient conditions, microorganisms regulate cellular activities to
[email protected],PhilippBaumann
maintain efficient growth. Efficiency is regarded as correlated with fast re-
MicrosoftProjectiswidelyusedfortemporalschedulingandresourceallo- production. Viaanoptimizationmodelofthewholecellwithanobjectiveto
cationofprojects. Weshowthatitsintegratedresource-allocationprocedure maximizegrowthrate,wepredictmacrofeaturesofmicrobesatgivennutri-
usesneithertheserialnortheparallelschedule-generationscheme, andthat entconcentrationsbyrepresentingessentialpathwayswithmodules. This,as
theprocedureperformsrelativelypoor. Wepresentabi-directionalschedule- knowntous,isthefirsttimegrowthrate,sizeandshapearepredictedhaving
improvementheuristic. Computationalresultsforaconstructionprojectand onlyintrinsicphysicalpropertiesofmoleculesasconstraints.
fortheJ30,J60,andJ120instancesfromPSPLIBindicatethatthisheuristic
shortenstheprojectdurationconsiderably.
2- Robustmodeldevelopmentfornon-linearmodels
2- Exactmethodsforresourcelevellingproblems MagderievanderWesthuizen,SchoolofComputer,Statistical
andMathematicalSciences,North-WestUniversity,PrivateBag
JürgenZimmermann,OperationsResearch,TUClausthal,
X6001,2520,Potchefstroom,SouthAfrica,
Julius-AlbertStr.2,38678,Clausthal-Zellerfeld,Germany,
[email protected],GielHattingh,Hennie
[email protected],ThorstenGather
Kruger
Wepresentexactsolutionmethodsforresourcelevellingproblemswithmin-
imumandmaximumtimelagsamongtheprojectactivities. Inparticular,we Thepredictivecapabilityofregressionmodelsreliesheavilyontheapplicabil-
consideratimewindowbasedenumerationmethodandtwotree-basedbranch- ityoftheassumptionsmadebythemodelbuilder. Inaddition,thepresence
and-boundproceduresbothwithasophisticatedconstructivelowerbound.Fur- ofoutliersmayalsoleadtomodelsthatarenotreliable. Thisstudyreports
thermore,weproposeamixedintegerlinearprogrammingformulationthatcan onrobusttechniquesappliedtominimalassumptionregressionmodelsinan
besolvedbystandardsolverssuchasCPLEX.Allapproachesarecomparedin efforttoimprovepredictivecapability. Theapproachisbasedonmathemat-
acomprehensivecomputationalstudyusingwellknowntestsetsfromlitera- icalprogrammingtechniquescombinedwithsmoothingandpiecewiselinear
ture.Instanceswithupto30activitiescouldbesolvedtooptimality. techniques.Differentcasesfromtheliteratureareconsideredandpresentedas
illustrativeexamples.
3- Temporal scheduling of concurrent engineering
3- A Bilevel Competitive Facility Location Model with
projects
Competitor’sResponse
ChristophSchwindt,InstituteofManagementandEconomics,
ClausthalUniversityofTechnology,Julius-Albert-Str.2,38678, HandeKucukaydin,IndustrialEngineering,BogaziciUniversity,
Clausthal-Zellerfeld,Germany, BogaziciUniversityIndustrialEngineeringDepartment,
[email protected],PhilippBenke Bebek-Istanbul-Turkey,34342,Istanbul,Turkey,
[email protected],NecatiAras,I.KubanAltinel
The concurrent engineering approach is intended to shorten the cycle time
of development projects by parallelizing consecutive development phases. We are concerned with a problem in which a new entrant leader firm aims
We consider the tradeoff between the time savings enabled by overlapping atfindingthelocationandattractivenessofeachnewfacilitytomaximizeits
precedence-relatedprojectactivitiesandtheincreaseintheactivitydurations profitwherethereareexistingfacilitiesbelongingtoacompetitor. Thecom-
thatistypicallyincurredbyadditionalintegrationandcoordinationefforts.We petitorreactstotheleaderbyadjustingtheattractivenesslevelsofitsexisting
investigatestructuralpropertiesofthetemporalschedulingproblemandex- facilitiestomaximizeitsprofit.Wefirstformulateabilevelmixed-integernon-
plainhowearliestandlateststartandcompletiontimesoftheactivitiescanbe linearprogrammingmodel.Then,weconvertitintoanequivalentsinglelevel
determinedefficientlybasedonlabel-correctingalgorithms. mixed-integernonlinearprogramandsolveitusingglobaloptimizationmeth-
ods.
4- IntegratedSchedulingandStaffingIT-Projects
RainerKolisch,TUMSchoolofManagement,Technische
(cid:4)
UniversitaetMuenchen,Arcisstr.21,80333,Muenchen, MA-10
Germany,[email protected],ChristianHeimerl
Monday,9:00-10:20
In this paper we present an optimization model to address the problem of 6.2.56
schedulingtheactivitiesofmultipleIT-projectswithserialstructuresandas-
signingtheprojectworktomulti-skilledinternalandexternalhumanresources Graphs and Networks I
withstaticandheterogeneousefficiencies. Themixed-binarylinearprogram
issolvedusingILOGCPLEXandahybridmetaheuristic. Thelatteremploys Stream: GraphsandNetworks
anefficientevaluationfunctionexploitingthenetworkstructureofthestaffing
Invitedsession
subproblem. Weassesstheimpactsofseveralproblemparametersoncompu-
tationtimeandsolutiongaps. Chair:ReinhardtEuler,Informatique,UniversitédeBrest,20av.Le
Gorgeu,BP817,29285,Brest,France,[email protected]
4
EURO24-Lisbon2010 MA-11
Statutoryinfectiousdiseasesbreakoutnotonlyaffectspeople’shealthandlives,
1- OnthePowerofDecompositionfortheMaximumInde-
butalsostagnatestheeconomicgrowth.Theprevalenceofinfectiousdiseases
pendentSetProblem also provides the development opportunities of biotechnology corporations.
TheeffectofthestatutoryinfectiousdiseasesoutbreakonTaiwanesebiotech-
AndreasBrandstädt,UniversitätRostock,18055,Rostock,
nologystockpricemovementsisexamined.Theempiricalresultspointoutthat
Germany,[email protected]
thereexistsasignificantlypositiveabnormalreturnofTaiwan’sbiotechnology
(jointworkwithC.T.Hoang,V.B.Le,V.V.Lozin,andR.Mosca)Inafiniteundi- industrybecauseofthestatutoryinfectiousepidemic.
rectedgraphG=(V,E)avertexsetSis’independent’(or’stable’)ifthevertices
inSaremutuallynonadjacent.ForgivenG,theMAXIMUMINDEPENDENT
SET(MIS)ProblemasksfoanindependentvertexsetofmaximumsizeinG. 2- Ahybridclassificationmethod: Usingasupportvector
TheMWSproblemasksforanindependentsetwithmaximumvertexweight; machineforruleextractionondiabetesdiagnosis
theMISproblemistheMWSproblemwithunitweights. Itiswellknown
thatMWS(MIS,respectively)isintractableandhardtoapproximate. Wedis- Chien-hsinYang,DepartmentofIndustrialEngineeringand
cussvariousdecompositiontechniquessuchascliqueseparatordecomposition, Management,OverseasChineseUniversity,100,ChiaoKwang
modulardecompositionandsplitdecompositionforsolvingtheMWSprob-
Rd.,Taichung40721,Taiwan,Taiwan,
lemefficientlyonvariousparticulargraphclasses. Itiswellknownthatthe
[email protected],Chun-ChinHsu
abovementioneddecompositionsarehelpfultoolsforsolvingtheMWSprob-
lem.Oneofourresultsallowstocombinecliqueseparatordecompositionand
modulardecomposition.Thisimpliesvariousimprovementsofknownresults, Manyofthefactorsrelatedtodiabetesmellitus(DM)havebeendiscovered
amongthemapolynomialtimealgorithmforMWSonapple-freegraphswhich fromasuccessionofstudiesinepidemiology. However,itseemsthattheus-
areacommongeneralizationofchordalgraphs,cographsandclaw-freegraphs. abilityandexplainabilityofmethodsareinferiortorulesextraction.Asupport
Finallywementionsomeopenproblems. vectormachinebasedhybridclassificationmethodisemployedtoextractrules
forDMdiagnosis. Toevaluateperformance,C5andback-propagationneural
networkswereusedasbenchmarks.Resultsfromthehybridapproachdemon-
2- Solving efficiently the weighted stable-set problem in
stratehighaccuracyandfidelity,andtherulescanhelpforpreventivemedicine
claw-freegraphsusingareductionoperation inDMdiagnosis.
PaoloNobili,Mathematics,UniversityofLecce,ViaArnesano,
73100,Lecce,Italy,[email protected],AntonioSassano
3- Applicationofartificialneuralnetworkandsupportvec-
Maximumweightstablesetscanbecomputedinpolynomialtimeforclaw-free tormachinetoclassifytheriskofdeathofhospitalized
graphs(Minty,Nakamuraetal.,Schrijver,Orioloetal.).Inthispaperwedefine patientswithacutecoronarysyndrome
thestronglyreduciblecliques,extendingtotheweightedcaseareductionop-
erationofLovaszandPlummer.Weusetheoperationforobtainingmaximum
RodrigoCollazo,OperationalResearch,CASNAV/UFRJ,Costa
weightalternatingpathsthroughmatchingcomputations. Weembedthepro-
DoriaSt,17,21910-170,RiodeJaneiro,RiodeJaneiro,Brazil,
cedureinaniterativeapproachthatcontructsagivenclaw-freegraphGnode
bynode,maintainingtheassociatedmaximumweightstableset.Theresulting [email protected],BasílioPereira,LauraBahiense,
algorithmhascomputationalcomplexityO(n4log(n)). AmáliaFariadosReis,AmáliaFariadosReis
3- ReconstructionofPermutationsRespecttosomeGen- Thisstudydevelopedanartificialneuralnetworkmodelandasupportvector
machinemodeltoclassifytheriskofdeathofhospitalizedpatientswithacute
eratorSetsoftheSymmetricGroup
coronarysyndromeathighandlow.Itwasusedthemutualinformationfeature
AlparVajkKramer,DEIO,FCUL,Portugal,[email protected] selectorunderuniforminformationdistributioncriteria(MIFS-U)forselection
ofthemostimportantinputvariables.Thecomputationalresultsshowabetter
We will consider the reconstruction of permutations regarding some special performanceofthesupportvectormachinemodelcomparedwiththeartificial
generatorsetsofthesymmetricgroup. Thegeneratorsetsconsideredarepar- neuralnetworkmodelandindicatetheinputvariablesage,creatinineandany
ticularsubsetsofinvolutionssuchasthereversals,prefixreversals,bubblere- priorrevascularizationasthemostrelevant.
versalsorCoxetergeneratorsandtranspositions. Thecommonpropertyofall
thisgeneratorsetsisthattheircorrespondingCayleygraphdoesnotcontain
triangles. 4- PredictioninMedicine: StatisticalModelsversusArtifi-
cialNeuralNetworks
(cid:4) AnaPapoila,BioestatísticaeInformática,FaculdadeCiências
MA-11
MédicasdaUniversidadeNovadeLisboa,CEAUL,Portugal,
Monday,9:00-10:20 [email protected],CarlosGeraldes,PatriciaXufre
8.2.38
Artificial Neural Networks are often used in Biomedical Sciences and
Emerging Data Mining Applications in Medicine. Amaingoalistopredictaclinicaloutcomeaftertakingintoac-
countasetofindependentexplanatoryvariables.ANNsariseasanalternative
Biomedics and Biotech to logistic regression. This study compare Generalized Linear Models with
binaryresponse,withtheperformanceofANNs,inwhatconcernstheirpre-
Stream: EmergingApplicationsofOR
dictiveanddiscriminativepower. Forbothapproaches,validationtechniques
Invitedsession wereapplied. Thesemethodologieswereusedtopredictmortalityofpatients
admittedtoanIntensiveCareUnitlocatedinLisbon.
Chair:HonoraSmith,SchoolofMathematics,Universityof
Southampton,Highfield,SO171BJ,Southampton,Hampshire,
UnitedKingdom,[email protected] 5- A Study in Different Channels’ Consumer on the Pur-
Chair:Gerhard-WilhelmWeber,InstituteofAppliedMathematics, chasingIntentionandBehaviorofBio-technologyProd-
MiddleEastTechnicalUniversity,ODTÜ,06531,Ankara,Turkey, ucts
[email protected]
YuanchauLiour,LogisticsManagement,TakmingUniversityof
Chair:VeronicaBiga,DepartmentofAutomaticControlandSystems
ScienceandTechnology,11451,Taipei,Taiwan,
Engineering,TheUniversityofSheffield,MappinStreet,S13JD,
[email protected],Chiao-LingHuang,Chie-beinChen
Sheffield,Afghanistan,v.biga@sheffield.ac.uk
Biotechnologyhasbeenplayinganimportantroleinmodernfinancialsoci-
1- The Information Effect of the Infectious Diseases Out-
ety;recently,asimprovementofeconomyenvironmentandthedevelopment
breakonBiotechnologyStockPerformance oftechnology,thegovernmentiscommittedtotheimplementationofbiotech-
nology. Weexploretheimpactofconsumerattitude,consumer’spurchasing
Yi-HsienWang,DepartmentofBanking&Finance,Chinese
intention,promotionsandproductinvolvement,andperceiveriskonpurchas-
CultureUniversity,55,Hwa-KangRoad,Yang-Ming-Shan., ingintention. WetakeNorthernTaiwanarea’sconsumerastheresearchob-
Taipei,Taiwan11114,R.O.C,11114,Taipei,Taiwan, jects,useSEMtoanalyzeandmakesuggestionstobio-technologyhealthfood
[email protected],Fu-JuYang,Kuang-HusnShih, companiesinaccordancewiththeempiricalconclusions.
Li-JeChen
5
MA-12 EURO24-Lisbon2010
(cid:4)
MA-12
Monday,9:00-10:20
8.2.39 (cid:4) MA-13
AHP 01 Monday,9:00-10:20
2.2.21
Stream: AnalyticHierarchyProcesses,AnalyticNetwork
Processes Location and GIS
Invitedsession
Stream: LocationAnalysis
Chair:GrzegorzGinda,Dept.ofOperationalResearchin
Invitedsession
Management,OpoleUniversityofTechnology,Facultyof
ManagementandProductionEngineering,ul.Warynskiego4, Chair:IoannisGiannikos,BusinessAdministration,Universityof
45-057,Opole,Poland,[email protected] Patras,UniversityofPatras,GR-26500,Patras,Greece,
[email protected]
1- AviationandtheBelgianClimatePolicy(ABC)-AMul-
ticriteriaAnalysis(MCA)fortheevaluationofpolicyop- 1- Enhancing Location Optimization Modeling Capabili-
tions to mitigate the total aviation climate change im- tiesthroughtheuseofGIS
pact
AlanMurray,GeographicalSciencesandUrbanPlanning,
AnnaliaBernardini,MOSI-T,VrijeUniversiteitBrussel, ArizonaStateUniversity,P.O.Box875302,85287-5302,Tempe,
Pleinlaan2,1050,Brussels,VlaamseBrabant,Belgium, AZ,UnitedStates,[email protected]
[email protected],TomVanLier,Annelies
Theprevalenceofwidelyavailableandaccessiblegeographicinformationsys-
Heemeryck,EllenVanHoeck,CathyMacharis
tem(GIS)packagesandassociatedgeographicdatahasbeenimportanttoall
TheABCprojectanalysesthedifferentclimatepolicyoptionsaimedtoreduce disciplinesthatstudy,analyzeandevaluatespatialproblems. Inthispaperwe
theclimatechangeimpactsoftheaviationsector. Inviewtocomparethedif- summarizemajorcharacteristicsofGISrelevanttolocationmodelingandspa-
ferentalternativepolicies(finan.&econ. tools,R&D,operat. procedures)the tialoptimization. Anumberofwidelyrelieduponoptimizationmodelsare
MCAmethodisapplied. Theperformancesofthosepoliciesareevaluatedin detailed. Particularattentionisgiventoidentifyingimplementationandap-
relationtosomeappropriatecriteria(env. performances,social-economicim- plicationlimitations,andhowthesecanbeovercomethroughintegrationwith
pactsaviationsector).AcombinationoftheAnalyticHierarchyProcessandthe GIS.
PROMETHEEmethodallowstocometoadetailedanalysisoftheadvantages
anddisadvantagesofeachoftheproposedpolicymeasures. 2- The Geographical Information System ’Ptolemeos-
Europe’andtheanalysisofregionalgeo-economicdy-
2- A consistency-based method for aggregating prefer-
namicsofFrance
ence information from multiple pairwise comparison
matrices JohnKarkazis,BusinessSchool,UniversityoftheAegean,
Chios,GR-82100,Chios,Greece,[email protected]
EstherDopazo,LenguajesySistemasInformáticos,Universidad
PolitecnicaMadrid,FacultadInformática,Campusde Thispaperexplorestheregionalgeo-economicdynamicsofFranceduringthe
period1985-2004employingGIS"Ptolemeos-Europe’. Inthebeginning,the
Montegancedo,28660,BoadilladelMonte,Madrid,Spain,
keynotionofregionalefficiencyisintroducedaswellasotherkeyregional
edopazo@fi.upm.es,MauricioRuiz-Tagle
analysisnotionssuchas: regionaldiscriminationcostandregionaldiscrimi-
Weconsideragroupdecisionproblem,wheredecisionmakersestimatetheir nationiso-curves. Basedonthenotionofregionalefficiencythegeneralgeo-
preferencesofasetofalternativesintotheformofpairwisecomparisonmatri- economicgravitymodelisintroducedanditsoutcome,thegeo-economicgrav-
ces(awell-establishedtechniqueinthisfield). Inthisscenario,afundamen- itycentersandotherrelatedstrategicanddynamicnotionssuchasthecapital
talproblemisthegenerationofapriorityvectorforthealternativesfromthe displacementfactorandthevelocityofgeo-economicgravitycentersarepre-
pairwisematriceswhichrepresentstheconsensusopinionforthegroup. We sentedanddiscussed. TheaboveareappliedtoFranceinordertoexplorethe
proposeaweightedlogarithmicgoalprogrammingmethodforaggregatingin- strategicgeo-economictrendsofthe22administrativeregionsofit.
dividualopinionsintoanoptimalgrouppriorityvector,wheretheconsistency
ofeachexpertistakenintoconsideration. 3- Improving the efficiency of WEEE collection systems
usingaweb-basedGISapplication
3- An agreement-based approach for generating priority
vectorsfrommultiplepairwisecomparisonmatrices SimãoRibeiro,ProductionandSystemsDepartment,University
ofMinho,Portugal,UniversidadedoMinho,CampusdeGualtar,
MauricioRuiz-Tagle,FacultaddeCs.delaIngeniería,
4710-057,Braga,Portugal,[email protected],Jorge
UniversidadAustraldeChile,GeneralLagos2086,Campus
Pereira,JoelCarvalho,JoséOliveira,ManuelFigueiredo,José
Miraflores,Valdivia,Chile,[email protected],EstherDopazo
Telhada,LuisDias
Theproblemofimportanceweightsanalysisanddeterminationfrommultiple
source information is a critical issue in many fields such as machine learn- Thisprojectfocusesonthedesignofaweb-basedGISapplicationtosupport
ing,meta-searchengines,multi-criteriadecisionmaking,etc.Wefocusonthe theplanningandmanagementofcollectingwasteofelectricalandelectronic
problemofcomputingtheimportanceweightsandthecorrespondingrankor- equipments(WEEE)networks.Itaddressestheissuesofgatheringandmanag-
deringofasetofalternativesfrominformationgivenbyagroupofexperts inginformationneededbynetworkoptimizationmodulesbeingincludedinan
intotheformofpairwisecomparisonmatrices.Wepresentanapproachbased integratedcomputerizedapplication,andtheissuesofanalyzingandmapping
onlpdistance-basedaggregationfunctionsandontheuseofconsensus-driven theiroutputs. SeveralGISanddatabasetechnologieswillbeused,andtheir
weightsforquantifyingtherelativeimportanceoftheexperts. applicabilityandutilitywillbediscussed.Inoverall,itisexpectedthatrelevant
economicandenvironmentalbenefitswillbeachieved.
4- IntegratedMADAAssessmentTool
4- MultiobjectiveDemandCoveringModelsbasedonGIS
GrzegorzGinda,Dept.ofOperationalResearchinManagement,
OpoleUniversityofTechnology,FacultyofManagementand IoannisGiannikos,BusinessAdministration,Universityof
ProductionEngineering,ul.Warynskiego4,45-057,Opole, Patras,UniversityofPatras,GR-26500,Patras,Greece,
Poland,[email protected],MiroslawDytczak [email protected],GeorgiosAlexandris
Integratedtoolforinterdisciplinaryassessmentofdecisionalternativesinman- Inthispaperwediscussanumberofmaximaldemandcoveringmodelswhere
agementandengineeringisdiscussedinthepaper.Thetoolmakesuseofsev- the customers as well as the servers may be geographic objects rather than
eralselectedMADAapproachestoobtainmorediversifiedresults.Acommon singlepoints. ThroughtheuseofGeographicInformationSystems(GIS),we
datastructureisappliedtomakepreparationofrequireddatalessexpensivein considerdifferentnotionsofcoverageanddevelopaseriesofmultiobjective
termsofbothtimeandworkeffort. Componentmethodsmakeitpossibleto programmingmodelsthattakeintoaccountthefollowingobjectives:(a)max-
includeandassessinfluenceofbothintangibleandtangibleaspects. Theyare imizationoftotalcoverage, (b)maximizationofminimumcoverageand(c)
alsoeasilyimplementable.Thetooladdressesissuesofinputdataconsistency minimizationofdistancetoserversofuncovereddemandobjects.Thesemod-
andgroupdecisionsupporttoo. Thetoolisuniquewithregardtoabilityof elstakeintoaccountthegeographyofeachdemandareainquestionandadjust
adaptationtoparticularneeds. Sampleanalysisisincludedwhichshowsits thelocationoftheserversaccordingly.
applicabilityandscaleofpotentialapplicationbenefits.
6
EURO24-Lisbon2010 MA-15
(cid:4) (cid:4)
MA-14 MA-15
Monday,9:00-10:20 Monday,9:00-10:20
2.2.15 2.2.12
Inventories in Supply Chains Location-routing problems
Stream: SupplyChainPlanning Stream: VehicleRouting
Invitedsession Invitedsession
Chair:HorstTempelmeier,SupplyChainManagementand Chair:ChristianPrins,LaboratoireLOSI,UniversitédeTechnologie
Production,UniversityofCologne,Albertus-Magnus-Platz,D-50923, deTroyes,BP2060,10010,TroyesCedex,France,[email protected]
Cologne,Germany,[email protected]
1- Centralized Distribution System of Infusion Solutions
1- A discrete time multi-level inventory system with a onaNetworkofHealthCareUnits
make-to-ordersupplier
WilliamGuerrero,IndustrialEngineering,Universidaddelos
HorstTempelmeier,SupplyChainManagementandProduction, Andes,AvCll147No17-81ap502,472,bogotá,bogotáD.C.,
UniversityofCologne,Albertus-Magnus-Platz,D-50923, Colombia,[email protected],NubiaVelasco,Ciro
Cologne,Germany,[email protected] AlbertoAmaya,ChristelleGueret,ThomasYeung
We study asupply network comprising afactory following a make-to-order Amethodologytoimproveinventorycontrolanddistributionpoliciesinhos-
strategy,awarehouseusingareorderpoint-reorderquantitypolicyanddistribu- pitalsispresented. Thestrategyistocentralizethemanagementofmedicines
tioncentersusingbase-stockpoliciesindiscretetime. Thefactoryismodeled intoasingledepottoreducecosts.Itisaimedtofindoptimalinventorycontrol
asadiscretetimeG/G/1queueingsystem.Thesystemisdecomposedintothree policiesforone-warehousen-retailerdistributionsystembasedonaMarkov
layersthatarelinkedthroughrandomwaitingtimes. Anoveralloptimization Chainmodel.Resultsareevaluatedonarealhospital.AnMIPmodeltodecide
modelincludingasdecisionvariablestheprocessingtimeinthefactoryand thelocationofthecentraldepotanddistributionroutestotheCareunitsisalso
theparametersoftheinventorypoliciesappliedinthedistributionsystemis proposed.Theobjectiveistheminimizationofthecostsoftheprojectandthe
formulatedandsolved. inventory-on-handvalueofthesystem.
2- Two-Capacitated-Supplier Two-Stage Periodic-Review 2- Solution methods for the periodic location-routing
SupplyChainProblemInvestigation problem
KaiLuo,OperationsManagement&InformationTechnology, CarolineProdhon,UniversityofTechnologyofTroyes,12rue
HECParis,1,ruedelaLibération,78351,JouyenJosas,Paris, MarieCurie,10000,Troyes,France,[email protected]
France,[email protected],LaoucineKerbache,Ramesh
Thewell-knownVehicleRoutingProblem(VRP)hasbeendeeplystudiedover
Bollapragada
thelastdecades. Nowadays,generalizationsaredevelopedtowardtacticalor
strategicdecisionlevelsbutnotboth. ThetacticalextensionorPeriodicVRP
Inthispaper,weinvestigateatwo-product(high-end,low-end),oneretailer/
(PVRP)plansasetoftripsoveramultiperiodhorizon.Thestrategicextension
twosuppliersproblemwithrandomdemandandperiodicreview. Theprob-
orLocation-RoutingProblem(LRP)ismotivatedbyinterdependentdepotloca-
lemisdecomposedintosub-modelsandsolvedsequentially.Forsimplecases,
tionandroutingdecisions.Thegoalhereistopresenttheveryrecentmethods
closedformexpressionsareprovidedfortheoptimalsolution. Weshowthat,
thatsolvethePeriodicLRP,acombinationofthePVRPandLRPintoaneven
undercertainconditions,theretailershouldplacethehigh-endproductinthe
morerealisticproblemcoveringalldecisionlevels.
secondaryinventory. Forcomplexcases,weproposeaheuristictosolvethe
problemandprovidemanagerialinsights.
3- Acuttingplaneapproachforthesingletruckandtrailer
routingproblemwithsatellitedepots(STTRPSD)
3- Heuristicsformulti-item,two-echeloninventorysystem
withaggregatemeanwaittimeconstraint. JuanG.Villegas,LOSI,UniversitedeTechnologiede
Troyes/UniversidaddelosAndes,12,rueMarieCurie,BP2060,
ArjunSubramaniam,AppliedMaterials,MountainView,
10010,Troyes,France,[email protected],JoseM.
California,UnitedStates,[email protected],
Belenguer,EnriqueBenavent,AntonioMartinezSykora,
DeepakBhatia
ChristianPrins,CarolineProdhon
Weconsideramulti-item,two-echelonsparepartsinventorysystem,withone IntheSTTRPSDatruckwitharemovabletrailerbasedatamaindepotserves
centralwarehouseandmultiplelocalwarehouses.Wepresentclose-to-optimal, thedemandofasetofcustomersreachableonlybytruck.Thus,beforeserving
scalableheuristicstominimizetotalcostwitheachlocalwarehousesubjectto thecustomersintruckroutes,itisnecessarytodetachthetraileratappropriate
anaggregatemeanwaittimeconstraint.Alllocationsoperateunderacontinu- parkingplacesandtotransferproductsbetweenthetruckandthetrailer. We
ousreviewsystemwithbasestockpolicies.Wetesteffectivenessbycomparing presentatwoindexformulationoftheSTTRPSDandvalidinequalitiesthat
withthelowerboundanddemonstratebetterperformancecomparedtoresults areusedwithinacuttingplanemethodtoproducelowerbounds,andtosolve
fromrecentlypublishedworks. theproblemwithbranchandcut.Theresultsarecomparedwithupperbounds
foundbyGRASP/VNDandILSon32randominstances
4- Price and Perception - Understanding the Consumer
SideofRecoveredProducts 4- AhybridGRASPxPathRelinkingfortheTwo-Echelon
LocationRoutingProblem
JonathanLinton,SchoolofManagement,UniversityofOttawa,
39SachsForestPlace,K2G6V2,Ottawa,Ontario,Canada, VietPhuongNguyen,LOSI-UniversitédeTechnologyde
[email protected],LeilaHamzaoui Troyes,Troyes,France,[email protected],Christian
Prins,CarolineProdhon
Weseektoaddressthegapinunderstandingconsumerwillingnesstopayfor
productsthatarecomprisedofrecoveredmaterialsandparts. Consequently,a ThispaperpresentsahybridbetweenGRASPandPathRelinkingtosolvethe
surveyof320respondentswasconductedtodeterminethewillingnesstopay Two-EchelonLocationRoutingProblem(LRP-2E).TheGRASPreinforcedby
fordifferenttypesofproductscontainingrecoveredmaterialsandcomponents. aLearningProcessusesthreeconstructiveheuristicstogeneratetheinitialsolu-
Aseriesofrelatedhypothesesareprovidedandtested.Inadditiontoconsider- tions.ThePath-relinkingaddsamemorymechanismbycombiningintensifica-
ingissuespersonalattitudestotheenvironmentandperceivedrisk,weconsider tionstrategyandpost-optimization.Ourmethoduseslocalsearchesstructured
theeffectsofbrandingandproductcharacteristics.Whiletheworkisempirical byaVariableNeighbourhoodDescent(VND).Computationalresultsconfirm
innatureitiscriticaltosupplychainplanningasthereislimitedresearchand theefficiencyofthisapproachontwosetsofLRP-2Einstances. Furthermore
understandingoftheconsumersideofclose-loopedsupplychains. itiscompetitivewiththebestmeta-heuristicpublishedfortheLRP.
7
MA-16 EURO24-Lisbon2010
(cid:4) (cid:4)
MA-16 MA-17
Monday,9:00-10:20 Monday,9:00-10:20
2.2.14 1.3.14
Rolling stock and Re-scheduling Collaborative Planning I
Stream: PublicTransport Stream: TransportationPlanning
Invitedsession Invitedsession
Chair:MarkusReuther,Optimization,Zuse-InstitutBerlin, Chair:HerbertKopfer,DepartmentofBusinessStudies&
Takustrasse7,14195,Berlin,Germany,[email protected] Economics,ChairofLogistics,UniversityofBremen,
Wilhelm-Herbst-Strasse5,28359,Bremen,Germany,
1- RollingStockRotationPlanningforIntercityRailTraffic [email protected]
Chair:MelanieBloos,ChairofLogistics,BremenUniversity,
MarkusReuther,Optimization,Zuse-InstitutBerlin,Takustrasse WilhelmHerbstStr.5,28359,Bremen,Germany,
7,14195,Berlin,Germany,[email protected] [email protected]
1- Transportation Operations Planning and Cost Alloca-
Weconsideroneofthebasicoperationalplanningproblemsinpublicrailtrans-
port,theconstructionofarollingstockschedule. Theproblemdealswiththe tioninaCooperativeScenario
optimizationoffeasiblerotationsforindividualrailcarsand,simultaneously,
AndreaNagel,Dept.ofInformationSystems,FernUniversität-
thecompositionoftrainsetsfromtheserailcars. Inaddition,wehavetointe-
UniversityofHagen,58084,Hagen,Germany,
grateserveralmaintenanceandregularityaspects.Modelingandcomputational
preliminiaryresultsforinstancesofourindustrialpartner,DBFernverkehrAG, [email protected],GiselherPankratz,Hermann
whichoperatesapproximately1.300trainsinEuropeperday,arepresented. Gehring
Cooperativescenariosintransportationplanningusuallyhavetocopewiththe
taskofsolvinganoptimizationproblem,aswellasfindingafairallocationof
2- Railway Rolling Stock Rescheduling with Rerouting of thecostsamongthepartners.Weidentifyandcharacterizetheseproblemsfora
Passengers real-lifecooperationoffourproducersinthefoodandbeveragesindustry,who
decidedtocoordinatetheirdistributionactivitiesbyinter-organisationaltrans-
GaborMaroti,DepartmentofDecisionandInformation portationplanning. Furthermore,wepresentasolutionmethodthathasbeen
implemented,integratingaGRASPheuristicwiththeShapleyvalueapproach.
Sciences,RotterdamSchoolofManagement,Erasmus
Finally,weshowcomputationalresults.
UniversityRotterdam,BurgOudlaan50,3062PARotterdam,
TheNetherland,3062PA,Rotterdam,Netherlands, 2- Allocating Cost of Service to Customers in Inventory
[email protected],LarsNielsen,LeoKroon Routing
Inthispresentationwedescribedisruptionmanagementprocessesforapas- OkanOzener,IndustrialEngineering,OzyeginUniversity,
sengerrailwaysystem.Inadisruptedsituation,thetimetable,therollingstock KusbakisiCadNo:2,AltunizadeUskudar,34662,Istanbul,
circulation,andthecrewdutiesmustberescheduled. Wefocusonreschedul- Turkey,[email protected],OzlemErgun,Martin
ingtherollingstockcirculation.Incaseofadisruption,thepassengersmaybe Savelsbergh
willingtotakeadetourroutearoundthedisruptedarea.Thentherollingstock
circulationmustberescheduledinsuchawaythatadditionalseatingcapacity Vendormanagedinventoryreplenishmentisacollaborationbetweenasupplier
isprovidedalongthedetourroute. Inthispresentationwedescribeanitera- anditscustomerswherethesupplierisresponsibleformanagingthecustomers’
tiveprocedurethatreroutesthepassengers,andthatmodifiestherollingstock inventorylevels. InourVMIsetting,thesupplierexploitssynergiesbetween
circulationaccordingly. Computationalresultsbasedonreal-lifeinstancesof customers,e.g.,theirlocations,usagerates,andstoragecapacities,toreduce
NetherlandsRailwayshaveshownthatthisproceduremaysubstantiallyreduce distribution costs. Due to the intricate interactions between customers, cal-
theirdelays. culatingafaircost-to-serveforeachcustomerisadauntingtask. However,
cost-to-serveinformationisusefulwhenmarketingtonewcustomers,orwhen
revisitingroutinganddeliveryquantitydecisions. Wedesignmechanismsfor
thiscostallocationproblemanddeterminetheircharacteristicsbothanalyti-
3- RapidTransitNetworks: TimeTableandRollingStock
callyandcomputationally.
ÁngelMarín,MatemáticaAplicadayEstadística,Universidad 3- Collaborative vehicle routing in a multi-depot environ-
PolitécnicadeMadrid,E.T.S.IngenierosAeronáuticos,Plaza ment
CardenalCisneros,3,28040,Madrid,Madrid,Spain,
JuliaRieck,DepartmentforOperationsResearch,Clausthal
[email protected],LuisCadarso
UniversityofTechnology,Julius-Albert-Str.2,38678,
Clausthal-Zellerfeld,Germany,[email protected]
Inrapidtransitnetworks, thedailyoperationsmanagementprocessincludes
two major tasks: 1. Train services Timetable (TT). 2. Rolling Stock (RS) Fiercecompetitionurgescarrierstocooperate.Particularly,medium-sizedcar-
assignmenttotheTT.Thetasksareinterdependentbutareoftensolvedse- riers only achieve the adequate area coverage by splitting transportation re-
quentiallyduetorestrictionsoncomputationaltimeandtheintractabilityofan questsintomultipletasks(pick-up,linehaul,delivery)thatcanbehandledsep-
integratedapproach. Inourmodelingapproachweconsidertheintegrationof aratelybydifferentcarriers. Hence,acarrierhastoperformthedeliveryand
TTandRS.Somecomputationalexperimentswillbepresented. pick-upservicesaroundthedepotwhileminimizingthetransportationcosts.In
ordertoimprovetheresultingsetofsingle-depotsolutions,wepresentanew
collaborativemethodthattriestofindareassignmentoftaskstocarrierswhich
4- Assignmentofservicesinbuslinesundercongestion decreasestheoveralltransportationcosts.
4- Theevaluationofpickupanddeliveryrequestsincases
EsteveCodina,StatisticsandOperationalResearch,UPC,Edifici
C5,Desp216CampusNord,08034,Barcelona,Spain, ofasymmetricinformation
[email protected],ÁngelMarín,FranciscoLopez MelanieBloos,ChairofLogistics,BremenUniversity,Wilhelm
HerbstStr.5,28359,Bremen,Germany,[email protected],
Amodelispresentedfordimensioningthenumberofservicesinbuslinesop- HerbertKopfer
eratingundercongestionedsituations,whichmayariseincaseofdisruptionof
Collaborativetransportplanningaimsatcreatingthemostefficientallocation
aRapidTransitNetwork. Themodeltakesintoaccountbuscapacitylimita-
ofrequeststocarriersforagroupagesystem. However,duetothenatureof
tionsandfleetavailabilityaswellasthedwelltimesofbusesatstations.Also,
thissystem,onlylimitedrelevantinformationonthecarriers’currentplanning
ananalysisofthewaitingtimeofpassengersatbusstopsismadewithspecial
isavailablesystem-wide.Ourresearchfocusesonevaluationcriteriathatcreate
emphasisonthisfactoronthemodelresults.Themodelisformulatedundera
anefficientsolutiondespiterestrictedinformationonthecarriers’situationand
system-optimumpointofviewandaheuristicalgorithmapproachisdeveloped
wepresentinitialresultsontheperformanceofevaluationcriteriaforindividual
forlargersizenetworks.
requests.
8
EURO24-Lisbon2010 MA-19
(cid:4) (cid:4)
MA-18 MA-19
Monday,9:00-10:20 Monday,9:00-10:20
1.3.15 1.3.20
New Achievements in Stochastic Models Game Theory and Economics
and Optimization
Stream: DynamicalSystemsandGameTheory
Stream: StochasticModelingandSimulation Invitedsession
Invitedsession Chair:Gerhard-WilhelmWeber,InstituteofAppliedMathematics,
Chair:ErikKropat,DepartmentofComputerScience,Universitätder MiddleEastTechnicalUniversity,ODTÜ,06531,Ankara,Turkey,
BundeswehrMünchen,Werner-Heisenberg-Weg39,85577, [email protected]
Neubiberg,Germany,[email protected] Chair:AlbertoA.Pinto,DepartamentodeMatematica,Universityof
Minho,EscoladeCiências,UniversidadedoMinho,4710-057,
1- InflationDerivatives: HJMFrameworkandMarketMod- Braga,Portugal,[email protected]
els
1- Investments under Oligopolistic Competition in a vin-
Kwai-sunLeung,SystemsEngineeringandEngineering tagedifferentialgame
Management,TheChineseUniversityofHongKong,Shatin, StefanWrzaczek,UniversityofTechnologyVienna,Instituteof
NewTerritories„HongKong,N.A.,HongKong,HongKong, MathematicalMethodsinEconomics,Argentinierstr.8,1.Stock
[email protected],LixinWu (ORDYS),1040,Vienna,[email protected],
PeterM.Kort
Inthispaper,weestablishaHeath-Jarrow-Morton(HJM)typeframeworkthat
governstheco-evolutionofthetermstructureofbothnominalandinflation Duetotechnologicalprogressnewmachinesaremoreproductive. Thusitis
rates. Pricingofinflationderivativesunderthisframeworkcanbecarriedout notonlyimportanttochosetheoptimalamountofinvestments,butalsotheop-
similarly to that of nominal interest-rate derivatives under the classic HJM timalage.Westudyanoligopolyconsistingoftwobigfirmsconnectedbythe
model. Based on the HJM framework, we further develop a market model pricetheygetfortheproducts.Inordertoincludethevintageeffectofinvest-
withsimpleforwardinflationratesusingdisplaceddiffusionprocesses,which mentswehavetocombinedistributedoptimalcontroltheorywithdifferential
resultsinclosed-formpricingforinflationcapletsandinflationswaptions.The gametheory. Forthetwoindependentvariables(ageandtime)theconceptof
smilemodelcanalsobedevelopedbasedonthemarketmodel. timeconsistencyhastobeconsideredforbothdirections.Importantresultsfor
bothdirectionscanbederivedandmotivated.
2- Onsomeantagonisticgamerelatedtomajorityvoting 2- Strategic Interaction in Macroeconomic Policies: An
ApplicationofDifferentialGameTheory
MichaelKhachay,UralBranchofRAS,InstituteofMathematics
KrishnaKumar,ManagingDirector,SamkhyaAnalyticaIndia
andMechanics,S.Kovalevskoy,16,620990,Ekaterinburg,
PvtLtd,110SobhaOpal39thCross,4thT-BlockJayanagar,
RussianFederation,[email protected]
560041,Bangalore,Karnataka,India,[email protected],Puja
Simplemajorityvotingisaclassicalapproachtoaggregationofindividualde- Guha
cisionssuggestedbyacommitteeofexperts. Inthispaper,stabilityofsucha
Theworldeconomyisnowhighlyconnected,enablingdevelopmentofdevel-
collectivedecision,s.t. exclusionofsomefixednumberofexperts,isinvesti-
opedanddevelopingcountries. Butitisaccompaniedbyrisksofpropagating
gated.LetsomegivenlistLofdecisionsbeacceptedbysomecommitteeofq
adverseshocksfromonecountrytoanother. Isolatedmacroeconomicpolicies
equivalentexperts,andletsomenumberk<qbefixed.Howsmallcanthecar-
guidedearlierthroughcontroltheoreticmodelsneedtobemodifiedintomod-
dinalityofthelargestsublistL’ofL,acceptablebyanyk-memberssubcommit-
elsofpolicycoordination.Exploitingtheconceptsofnon-cooperativesolution
tee,be?Tightlowerboundofthisquantitywillbepresented,it’sasymptotical
throughNash-Equilibrium,andcooperativesolutionthroughNashprogramin
behaviorandapplicationswillbediscussed.
differentialgameswithquadraticpay-offsweintroducestrategicinteractionin
macroeconomicpolicy.
3- Theeffectofcorrelationinmake-to-ordersystems
3- An optimal selection of watchman routes by search
MichaelZazanis,Statistics,AthensUniversityofEconomicsand game
Business,76Patissionstr.,10434,Athens,Greece, ShuheiMorita,Dep.ofComputerScience,NationalDefense
[email protected] Academy,1-10-20,Hashirimizu,239-8686,Yokosukacity,
KanagawaPrefecture,Japan,[email protected],Ryusuke
Westudytheeffectofcorrelationintheprocessingtimesofmake-to-ordersys-
Hohzaki,ToruKomiya,EmikoFukuda
temsusingmarkovianqueueingmodelsandmatrix-geometrictechniques.Par-
ticularemphasisisplacedonthecorrelatedprocesswithexponentialmarginals Thispaperdealswithanoptimalselectionofwatchmanroutesinafacility,such
derived from the Kibble-Moran-Downton bivariate exponential distribution. asartgallery. Artgalleryproblemisafamousprobleminthefieldofcom-
Bothexactresultsandlogarithmicasymptoticsarederivedforthesesystems. putationalgeometry, whichdecidesthestationarydeploymentofwatchmen.
Assemble-to-ordersystemswithcorrelateddemandsarealsoanalyzed. Thispaperconsidersadynamicpatrolplanforthefacilityfromtheviewpoint
ofOperationalResearch. First, weobtainanoptimalintrusionschedulefor
theminimumdetectionprobabilityoftheintruderbydynamicprogramming.
4- Rollover Optimization under Uncertain Regulatory Ap- Secondly,weformulateanoptimalselectionproblemofwatchmanroutesand
provalDateforProductswithBassDemandRate solveitbysearchtheoryandgametheory.
HibaElKhoury,OperationsManagementandInformation 4- Nonparametricpredictionofbankloanrecoveries
Technology,HEC-PARIS,HECParis,1ruedeLaliberation,
JoãoBastos,TechnicalUniversityofLisbon,CEMAPRE-ISEG,
78350,JouyenJosas,France,[email protected],
RuadoQuelhas6,1200-781,Lisboa,Portugal,
ChristianVanDelft,LaoucineKerbache
[email protected]
Consideracompanythatplanstophase-outanexistingproductandphase-in
WiththeadventoftheBaselIIAccord,bankingorganizationsareinvitedtoes-
areplacementone. Ifproductionoftheexistingproductisstoppedearly,the
timatecreditriskcapitalrequirementsusinganinternalratingsbasedapproach.
firmwillloseprofitandgoodwill. Yet,ifproductionoftheexistingproduct
Inordertobecompliantwiththisapproach,institutionsmustestimatetheex-
isstoppedlate,thefirmwillexperienceanobsolescencecostfortheexisting
pectedloss-given-default,thefractionofthecreditexposurethatislostifthe
product. WestudyrolloverofproductsthatfollowaBassdemandrate,with
borrowerdefaults.Thisstudyevaluatestheabilityofnonparametricregression
thenewproductsubjecttoanuncertainregulatoryapprovaldate.Weminimize
treemodelstoforecastbankloancreditlosses. Theperformanceofthemod-
costsassociatedwiththerolloveranddetermineoptimalrolloverstrategiesfor
elsisbenchmarkedagainstrecoveryestimatesgivenbyhistoricalaveragesand
differentproductfamilies.
parametricfractionalresponseregressions.
9
MA-20 EURO24-Lisbon2010
(cid:4) (cid:4)
MA-20 MA-21
Monday,9:00-10:20 Monday,9:00-10:20
1.3.33A 6.2.47
Cutting and Packing 1 OR in Practice I
Stream: CuttingandPacking Stream: SoftwareforOR/MS
Invitedsession Invitedsession
Chair:JoseFernandoOliveira,FacultyofEngineering/INESC Chair:AnaMoura,Economics,ManagementandIndustrial
Porto,UniversidadedoPorto,RuaDr.RobertoFrias,4200-465, Engineering,UniversityofAveiro,CampusUniversitáriode
Porto,Portugal,[email protected] Santiago,3810-193,Aveiro,Portugal,[email protected]
1- Radical-free phi-functions for 2D objects and their ap- 1- Optimizing Fire Station Locations for Istanbul
plications MetropolitanMunicipality
TatianaRomanova,DepartmentofMathematicalModelingand EmelAktas,IndustrialEngineeringDepartment,Istanbul
OptimalDesign,InstituteforMechanicalEngineeringProblems TechnicalUniversity,ITUIsletmeFakultesi,Macka,34367,
oftheNationalAcademyofSciencesofUkraine,2/10Pozharsky Istanbul,Turkey,[email protected],OzayOzaydin,SuleOnsel,
St.,61046,Kharkov,Ukraine,[email protected],Nikolai BurcinBozkaya,FusunUlengin
Chernov,YuriStoyan,A.Pankratov Istanbulisadenselypopulatedcitywith2000+yearsofculturalheritage. We
provideamax-covertypemathematicalmodelwithlimitedbudgettohelpMu-
Phi-functionsareusedtosolvepacking,cutting,andcoveringproblems. Our
nicipalityauthoritiesdeterminenewfirestationlocationsinadditiontoexisting
purposeistoconstructphi-functionsbyusingsimplemathematicalformulas
ones.WesolvethismodeltooptimalityusingGAMSandincreaseexistingfire
withoutradicals. Firstweintroduceaspecialclassofbasicobjectsandprove
coveragefrom56%to86%. Wealsoconsiderunlimitedbudget, overallre-
thatany2Dobjectwhosefrontierisformedbycirculararcsandlinesegments
location,andincreasedemphasisoncity’sculturaltreasures. WeuseGISto
mayberepresentedasaunionofbasicobjects. Thenwederiveacomplete
processallgeographicalinputdata,calculatenetworkdistancesandcoverage
classofradical-freephi-functionsforallpairsofbasicobjects.Lastlyweshow
ratios,andvisualizevarioussolutionsofourmodel.
howtoformphi-functionsformoregeneralobjects. Asoftwarepackageis
developedbasedontheseresults.Someapplicationsaregiven.
2- Designofaspatiallyexplicitmodeltooptimizethese-
lectionofreforestationprojectsandthesizingofade-
2- A constructive algorithm for leather nesting in the au-
tentiondamtoreducepeakrunoffinasmallwatershed
tomotiveindustry
JochenBreschan,DepartmentofEnvironmentalSciences,ETH
PedroBrás,UniversidadedoMinho,4710-057,Braga,Portugal,
Zurich,CHNK73.1,Universitaetstr.22,8092,Zurich,
[email protected],CláudioAlves,J.M.Valériode
Switzerland,[email protected],HansRudorfHeinimann,
Carvalho,TelmoPinto
RichardChurch
Weaddresstheleathernestingprobleminthecontextofanautomotivecom- We address the problem of reducing potential flood hazards within a small
pany. Inthis2-dimensionalproblem,irregularshapes(carseatscomponents) Alpine watershed, using combinations of 1) spatially explicit reforestation
havetobecutfromanaturalleatherhidewithholes,defectsandqualityzones. projects and 2) a detention dam at the outlet in order to reduce peak storm
Weproposeasolutionalgorithmbasedonaconstructiveprocedure. Wedis- runoff. Theobjectiveistooptimizethelocationofreforestationprojectsand
cussthedifferentaspectsofthisprocedureandexplainthestrategicoptionson thesizingofthedetentiondamtocost-effectivelymeettargetsofpeakrunoff
whichitisbased. Wealsobrieflydescribetheno-fitpolygonmethodusedto reduction. WeshowhowtocastthisproblemasaMixedInteger-LinearPro-
guaranteevalidplacementsintheleatherhides. Computationalresultsonreal grammingoptimizationmodelthatissolvedusingCPLEX.Finally,wepresent
instancesarepresented. anapplicationofthismodeltotheVogelbachwatershed(CH).
3- A Hybrid Meta-heuristic Approach for Non-standard 3- A two-stage packing procedure for a Portuguese trad-
PackingProblemswithAdditionalConditions ingcompany
GiorgioFasano,SpaceInfrastructures&Transportation,Thales AnaMoura,Economics,ManagementandIndustrial
AleniaSpaceItalia,Str.AnticadiCollegno253,10146,Turin, Engineering,UniversityofAveiro,CampusUniversitáriode
Italy,[email protected] Santiago,3810-193,Aveiro,Portugal,[email protected],
AndreasBortfeldt
Thisworkfocusesontheorthogonalpackingoftetris-likeitemswithinanon-
rectangulardomain(withforbiddenzones),inthepresenceofadditionalcondi- Thisworkreportsonthedevelopmentofaprototypicaldecisionsupportsys-
tions,suchasbalancing. Theoverallproblemisformulatedintermsofmixed tem,calledPackingandRoutingOptimizer(PRO),whichisdevisedtosolve
integerprogramming. Sincenontrivialcasesgiverisetoverylarge-scalein- severalpackingandroutingproblemsforaPortuguesecompany.Thedailydis-
stances,ahybridmeta-heuristicapproachhasbeenadoptedtosolverecursively tributionprocessisanalyzedandthreedecisionproblemsregardingautomated
theproblem.Itisbasedontheconceptofabstractconfiguration,derivingfrom decisionsupportaredetermined. Theperformanceofthesolutionapproaches
therelativepositionofitems.Anextensionconsidersthe2Dcaseofpolygons isevaluatedbycomputationaltestsbasedonactualcompanydata.Thetestre-
fromaglobaloptimizationpointofview. sultsshowthatthesystemisabletohelpimprovingthedailydecisionsandto
strengthentheflexibilityinnegotiationswithcustomers.
4- Dualfeasiblefunctionsforvectorpackingproblems
JürgenRietz,DepartamentodeProduçãoeSistemas,Centrode (cid:4) MA-22
InvestigaçãoAlgoritmi,UniversidadedoMinho,Campusde
Gualtar,4715-082,Braga,Portugal,[email protected], Monday,9:00-10:20
CláudioAlves,J.M.ValériodeCarvalho,FrançoisClautiaux 3.1.10
Dual-feasible functions (DFFs) were successfully used to obtain fast valid Teaching OR/MS
lower bounds for the one-dimensional cutting stock problem. To accelerate
thecalculations,onlymaximal,especiallyextremalfunctionsshouldbeused. Stream: TeachingOR/MS
Thisapproachworksforthevectorpackingproblemtoo,ifthedomainofthe
Invitedsession
DFFsisreplacedbyamore-dimensionalunitcube.Westatenecessaryandsuf-
ficientconditionsforsuchfunctionstobemaximalrespectivelyextremaland Chair:SusanaColaco,DepartamentodeCiênciasMatemáticase
presentsomenon-trivialexamples. NewDFFsfortheproblemarediscussed, Naturais,EscolaSueriordeEducação-Institutopolitécnicode
andcomputationalresultsarereported. Santarém,CompexoAndaluz,Apartado131,2000,Santarem,
Portugal,[email protected]
10