Advances in Metaheuristics PDF
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Operations Research/Computer Science Interfaces Series Luca Di Gaspero Andrea Schaerf Thomas Stützle Editors Advances in Metaheuristics Operations Research/Computer Science Interfaces Series Volume 53 SeriesEditors: RameshSharda OklahomaStateUniversity,Stillwater,Oklahoma,USA StefanVoß UniversityofHamburg,Hamburg,Germany Forfurthervolumes: http://www.springer.com/series/6375 Luca Di Gaspero • Andrea Schaerf Thomas Stu¨tzle Editors Advances in Metaheuristics 123 Editors LucaDiGaspero AndreaSchaerf DIEGM DIEGM UniversityofUdine UniversityofUdine Udine,Italy Udine,Italy ThomasStu¨tzle IRIDIA Universite´LibredeBruxelles Bruxelles,Belgium ISSN1387-666X ISBN978-1-4614-6321-4 ISBN978-1-4614-6322-1(eBook) DOI10.1007/978-1-4614-6322-1 SpringerNewYorkHeidelbergDordrechtLondon LibraryofCongressControlNumber:2013931180 (cid:2)c SpringerScience+BusinessMediaNewYork2013 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. 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Printedonacid-freepaper SpringerispartofSpringerScience+BusinessMedia(www.springer.com) Preface Metaheuristics have been a very active research topic for more than two decades. During this time many new metaheuristic strategies have been devised, they have been experimentally tested and improved on challenging benchmark problems, and they have proven to be important tools for tackling optimization tasks in a largenumberofpracticalapplications.Inotherwords,metaheuristicsarenowadays establishedasoneofthemainsearchparadigmsfortacklingcomputationallyhard problems.Still,therearealargenumberofresearchchallengesintheareaofmeta- heuristics.Thesechallengesrangefrommorefundamentalquestionsontheoretical propertiesandperformanceguarantees,empiricalalgorithmanalysis,effectivecon- figurationofmetaheuristicalgorithms,approachestocombinemetaheuristicswith otheralgorithmictechniques,towardsextendingthe available techniquesto tackle evermorechallengingproblems. This edited volume grew out of the contributions presented at the ninth Meta- heuristicsInternationalConferencethatwasheldinUdine,Italy,25–28July2011. Theconferencecomprised117presentationsofpeer-reviewedcontributionsand3 invited talks, and it was attended by 169 delegates. The chapters collected in this bookexemplifycontributionstoseveraloftheresearchdirectionsthatwehaveout- linedabove. Thefirstthreecontributionsdealwiththeanalysisandtheconfigurationofmeta- heuristics.ThearticleofLehreandWittpresentsfirststepstowardsthetheoretical run-timeanalysis of particle swarm optimization(PSO) algorithms,a well-known metaheuristictechniquethatismainlyusedtotacklecontinuousoptimizationprob- lems. In particular, they analyze PSO algorithms from the perspective of the first hittingtimeofa(small)regioninthesolutionspacearoundtheoptimum. Barbosa, Bernardino, and Barreto deal with techniques for analyzing the run- time behavior of metaheuristics. They discuss variants of performance profiles, a tool for the visualization and the interpretation of experimental results, and they viewperformancecomparisonsfromamulti-criteriaperspective. Gunawan, Lau, and Wong explore the possibility of using experimental de- signtechniquestoreducethesize oftheparameterspacethatautomaticalgorithm configuration techniques need to consider. Essentially, they propose to avoid the v vi Preface combinatorialexplosionoffullfactorialdesignsbyworkingonpartitionsofparam- eters and then restricting the domains of the parameters using fractional factorial designs.Intheircontributiontheyillustratetheirapproachusingonecasestudy. Thefollowingthreechaptersdescribeapplicationsofmetaheuristicstochalleng- ing problems. The inherent difficulty in these problems is due to the inclusion of multipleobjectivefunctions,dynamicdata,oramixofdifferenttypesofvariables. Wagner,Day,Jordan,Kroeger,andNeumannsearch forpacingstrategiesthatim- provetheperformanceofacyclingteaminteampursuittrackcycling.Thehardness of the problem arises from the simultaneous optimization of the sequence of ac- tionsthecyclistsshoulddo(i.e.,permutationsofintegervalues)andthepowerthey shouldinvest(i.e.,continuousvariables). Amorim,HenggelerAntunes,andAlmada–Loboexploretheintegrationofdual information into the mutation operator of a genetic algorithm. Their approach is appliedtoachallengingmulti-objectiveoptimizationproblemthatarisesinthepro- duction planning of perishable products. The main contribution of the paper is to showhowtoemploydualinformationfromamixed-integerprogrammingformula- tionoftheproblemtobetterdirectthemutationoperatorofamulti-objectivegenetic algorithm. Lepagnot, Nakib, Oulhadj, and Siarry propose a new metaheuristic technique, called multiple localsearch algorithm for dynamicoptimization(MLSDO), which has been applied for the solution of an image registration problem. In detail, the systemisdesignedtorecognizeabnormalitiesinthebrain,startingfromasequence ofcine-MRIregistrations.MLSDOusesseverallocalsearchestoexplorethesearch spaceandtotrackthefoundoptimaoverthedynamicmodificationsoftheobjective function.Inthisapproach,eachlocalsearchisperformedinparallel,andallsearches arecoordinatedbyadedicatedmodule. The final four chapters contribute new metaheuristic approaches to tackle dif- ficult combinatorial optimization problems. The first two deal with vehicle rout- ingproblems,arelevantclassofoptimizationproblemswheremetaheuristicshave reachedparticularlyhighsuccess. Crainic,Mancini,Perboli,andTadeiproposeanapproachbasedontheGRASP metaheuristic.In this work,GRASP is usedin combinationwith path relinkingto addressthe two-echelonvehicle routingproblem.This problemis an extensionof theclassicalvehicleroutinginwhichthedeliveryfromasingledepottocustomers is achieved by routing and consolidating the freight through intermediate depots, called satellites. The problem is treated by decomposition, separating the depot- to-satellitetransferfromthe satellite-to-customerdelivery.Theapproachappliesa GRASPandalocalsearchprocedureinsequence.Afterwards,theresultingsolution islinkedtoanelitesolutionbymeansofpathrelinking. Reinholz and Schneider tackle the open vehicle routing problem, whose main characteristicisthatvehiclesdonotreturntothedepotafterservingthelastclient. Theauthorsdefineaframeworkthatincludesseveralstandardneighborhoodstruc- tures that are based on a path exchange operator and that allows for an efficient computation of cost differences induced by the moves. The algorithmic approach uses these neighborhood structures in a stochastic multiple neighborhood search Preface vii andintegratesthelatterintoa(1+1)-evolutionarystrategy.Theperformanceofthis hybridstrategyisevaluatedonstandardbenchmarkinstancestakenfromliterature, provingthecompetitivenessofthemethod. PimmerandRaidldealwith anotherclassicalproblemthatprovedtobepartic- ularlyhardinpractice,namelythehigh-schooltimetablingproblem.Theapproach usedinthischapterisnotastandardmetaheuristicapproach,butacomplexheuris- tic composedby a constructivephase followed by a local search. Both phasesare appliedatthelevelofgroupsofeventsinthesametimeslot,inalarge-neighborhood fashion.Experimentalresultsonavailablebenchmarksindicatethatthisapproachis competitive. Kemmoe, Lacomme, Tchernev, and Quilliot use GRASP to address a supply chainoptimizationproblemwithadditionalfinancialconstraints.Inthissetting,the goalis to obtain the smallest duration of a supply chain operationalplanningthat respectsthebudgetlimits.Forthisspecificproblem,GRASPishybridizedwithan evolutionarylocalsearch.Themethodis evaluatedonasetofwidelyusedbench- marks,suitablymodifiedtotakeintoaccountthefinancialconstraints. The organizationof MIC 2011 and the edition of this post-conferencevolume wouldnothavebeenpossiblewithoutthehelpofalargenumberofpeople.Special cordialthanksgo to themembersof the localorganizingcommitteefortheir hard work in all preparatorytasks and the practicalorganizationof the conference.We alsowouldsincerelythankthespecialsessionorganizersforextendingtheconfer- enceprogramwithrelevanttopicsthatmadetheconferencemoreattractive,aswell as the program committee members and the additionalreferees for their qualified anddetailedreviews.Lastbutnotleast, wewouldliketothankalltheresearchers inmetaheuristicswhosubmittedandparticipatedintheconferenceand,inparticu- lar,whosubmittedtheirextendedversionsforconsiderationinthispost-conference volume:youarethemostimportanttoadvancethemetaheuristicsfieldandtomake metaheuristicresearchlively,inspiring,andenjoyable! Udine,Italy LucaDiGaspero Udine,Italy AndreaSchaerf Bruxelles,Belgium ThomasStu¨tzle Acknowledgements PrintedwithassistanceoftheDepartmentofElectrical,Management,andMechan- icalEngineeringoftheUniversityofUdine. ix
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