Local Search for Planning and Scheduling: ECAI 2000 Workshop, Berlin, Germany, August 21, 2000. Revised Papers

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Springer Science & Business Media, Nov 7, 2001 - Computers - 169 pages
Withtheincreasingdeploymentofplanningandschedulingsystems,developers oftenhavetodealwithverylargesearchspaces,real-timeperformancedemands, anddynamicenvironments. Completere'nementmethodsdonotscalewell,- kinglocalsearchmethodstheonlypracticalalternative. Adynamicenvironment alsopromotestheapplicationoflocalsearch,thesearchheuristicsnotnormally beinga'ectedbymodi'cationsofthesearchspace. Furthermore,localsearchis wellsuitedforanytimerequirementsbecausetheoptimizationgoalisimproved iteratively. Suchadvantagesareo'setbytheincompletenessofmostlocalsearch methods,whichmakesitimpossibletoprovetheinconsistencyoroptimalityof thesolutionsgenerated. Popularlocalsearchapproachesincludeevolutionary- gorithms,simulatedannealing,tabusearch,min-con'icts,GSAT,andWalksat. The'rstarticleinthisbook-aninvitedcontributionbyStefanVoß-givesan overviewofthesemethods. ThebookisbasedonthecontributionstotheWorkshoponLocalSearchfor Planning&Scheduling,heldonAugust21,2000atthe14thEuropeanCon- renceonArti'cialIntelligence(ECAI2000)inBerlin,Germany. Theworkshop broughttogetherresearchersfromtheplanningandschedulingcommunitiesto explorethesetopicswithrespecttolocalsearchprocedures. Aftertheworkshop, asecondreviewprocessresultedinthecontributionstothepresentvolume. Voß''soverviewisfollowedbytwoarticles,byHamiezandHaoandGerevini andSerina,onspeci'c"classical"combinatorialsearchproblems. Thearticleby HamiezandHaoaddressestheproblemofsports-leaguescheduling,presenting results achieved by a tabu search method based on a neighborhood of value swaps. GereviniandSerina''sarticleaddressesthetopicthatdominatestherest ofthebook:actionplanning. Itbuildsontheirpreviousworkonlocalsearch onplanninggraphs,presentinganewsearchguidanceheuristicwithdynamic parametertuning. Thenextsetofarticlesdealwithplanningsystemsthatareabletoinc- porateresourcereasoning. The'rstarticle,ofwhichIamtheauthor,makesit clearwhyconventionalplanningsystemscannotproperlyhandleplanningwith resourcesandgivesanoverviewoftheconstraint-basedExcaliburagent''spl- ningsystem,whichdoesnothavetheserestrictions. Thenextthreearticlesare aboutNASAJPL''sASPEN/CASPERsystem. The'rstone-byChien,Knight, andRabideau-focusesonthereplanningcapabilitiesoflocalsearchmethods, presentingtwoempiricalstudiesinwhichacontinuousplanningprocessclearly outperformsarestartstrategy. Thenextarticle,byEngelhardtandChien,shows howlearningcanbeusedtospeedupthesearchforaplan. Thegoalisto'nda setofsearchheuristicsthatguidethesearchaswellaspossible. Thelastarticle inthisblock-byKnight,Rabideau,andChien-proposesanddemonstrates, a technique for aggregating single search moves so that distant states can be reachedmoreeasily. VI Preface Thelastthreearticlesinthisbookaddresstopicsthatarenotdirectlyrelated tolocalsearch,butthedescribedmethodsmakeverylocaldecisionsduringthe search. RefanidisandVlahavasdescribeextensionstotheGRTplanner,e. g. ,a hill-climbingstrategyforactionselection. Theextensionsresultinmuchbetter performancethanwiththeoriginalGRTplanner. Thesecondarticle-byO- india, Sebastia, and Marzal - presents a planning algorithm that successively re'nes a start graph by di'erent phases, e. g. , a phase to guarantee comp- teness. Inthelastarticle,HiraishiandMizoguchipresentasearchmethodfor constructingaroutemap. Constraintswithrespecttomemoryandtimecanbe incorporatedintothesearchprocess. Iwishtoexpressmygratitudetothemembersoftheprogramcommittee, whoactedasreviewersfortheworkshopandthisvolume. Iwouldalsoliketo thank all those who helped to make this workshop a success - including, of course,theparticipantsandtheauthorsofpapersinthisvolume. June2001 AlexanderNareyek WorkshopChair ProgramCommittee EmileH. L. Aarts PhilipsResearch Jos ́eLuisAmbite Univ. ofSouthernCalifornia BlaiBonet UniversityofCalifornia RonenI. Brafman Ben-GurionUniversity SteveChien NASAJPL AndrewDavenport IBMT. J. Watson AlfonsoGerevini Universit`adiBrescia HolgerH. Hoos Univ. ofBritishColumbia AlexanderNareyek GMDFIRST AngeloOddi IP-CNR Mar ́?aC. Ri? Univ. T ́ec. Fed. SantaMar ́?a BartSelman CornellUniversity EdwardTsang UniversityofEssex TableofContents InvitedPaper Meta-heuristics:TheStateoftheArt. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 StefanVoß CombinatorialOptimization SolvingtheSportsLeagueSchedulingProblemwithTabuSearch . . . . . . . . 24 Jean-PhilippeHamiez,Jin-KaoHao LagrangeMultipliersforLocalSearchonPlanningGraphs . . . . . . . . . . . . . . 37 AlfonsoGerevini,IvanSerina PlanningwithResources BeyondthePlan-LengthCriterion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 AlexanderNareyek AnEmpiricalEvaluationoftheE'ectiveness ofLocalSearchforReplanning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 SteveChien,RussellKnight,GreggRabideau Board-LayingTechniquesImproveLocalSearch inMixedPlanningandScheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 RussellKnight,GreggRabideau,SteveChien EmpiricalEvaluationofLocalSearchMethods forAdaptingPlanningPoliciesinaStochasticEnvironment. . . . . . . . . . . . . 108 BarbaraEngelhardt,SteveChien RelatedApproaches TheGRTPlanner:NewResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 IoannisRefanidis,IoannisVlahavas IncrementalLocalSearchforPlanningProblems. . . . . . . . . . . . . . . . . . . . . . . 139 EvaOnaindia,LauraSebastia,EliseoMarzal MapDrawingBasedonaResource-ConstrainedSearch foraNavigationSystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 HironoriHiraishi,FumioMizoguchi AuthorIndex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Meta-heuristics:TheStateoftheArt StefanVoß TechnischeUniversit ̈atBraunschweig Institutfur ̈ Wirtschaftswissenschaften Abt-Jerusalem-Straße7 D-38106Braunschweig,Germany stefan. voss@tu-bs. de Abstract.

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