Stochastic Local Search : Foundations & Applications (The Morgan Kaufmann Series in Artificial Intelligence)

677 Pages·2004·8.64 MB·English

by  Holger H. Hoos

PraiseforStochasticLocalSearch:FoundationsandApplications
‘HoosandStützle,twomajorplayersinthefield,provideuswithanexcellentoverview
ofstochasticlocalsearch.Ifyouarelookingforabookthatcoversallthemajormeta-
heuristics,givesyouinsightintotheirworkingandguidesyouintheirapplicationtoa
widesetofcombinatorialoptimizationproblems,thisisthebook.’
MarcoDorigo,UniversitéLibredeBruxelles
‘Stochastic Local Search: Foundations and Applications provides an original and
synthetic presentation of a large class of algorithms more commonly known as meta-
heuristics.Overthelast20years,thesemethodshavebecomeextremelypopular,often
representingtheonlypracticalapproachfortacklingsomanyofthehardcombinatorial
problemsthatareencounteredinreal-lifeapplications.HoosandStützle’streatmentof
thetopiciscomprehensiveandcoversavarietyoftechniques,includingsimulatedan-
nealing,tabusearch,geneticalgorithmsandantcolonyoptimization,butamainfeature
of the book is its proposal of a most welcome unifying framework for describing and
analyzingthevariousmethods.’
MichelGendreau,UniversitédeMontréal
‘Local search algorithms are often the most practical approach to solving constraint
satisfaction and optimization problems that admit no fast deterministic solution. This
book is full of information and insights that would be invaluable for both researchers
andpractitioners.’
HenryKautz,UniversityofWashington
‘Thisextensivebookprovidesanauthoritativeanddetailedexpositionfornovicesand
expertsalikewhoneedtotackledifficultdecisionorcombinatorialoptimizationprob-
lems.Thechaptersspanfundamentaltheoreticalquestionssuchas,“Whenandwhydo
heuristics work well?” but also more applied aspects involving, for instance, the com-
parison of very different algorithms. The authors are university faculty members and
leading players in their research fields; our communities will enjoy in particular their
book’svaluableteachingmaterialanda“complete”bibliographyofthestateoftheart
forthefield.’
OlivierMartin,UniversitéParis-Sud,Orsay
‘Theauthorsprovidealucidandcomprehensiveintroductiontothelargebodyofwork
on stochastic local search methods for solving combinatorial problems. The text also
covers a series of carefully executed empirical studies that provide significant further
insightsintotheperformanceofsuchmethodsandshowthevalueofanempiricalsci-
entificmethodologyinthestudyofalgorithms.Anexcellentoverviewofthewiderange
ofapplicationsofstochasticlocalsearchmethodsisincluded.’
BartSelman,CornellUniversity
‘Stochasticlocalsearchisapowerfulsearchtechniqueforsolvingawiderangeofcombi-
natorialproblems.Ifyouonlywanttoreadonebookonthisimportanttopic,youshould
readHoosandStützle’s.Itisacomprehensiveandinformativesurveyofthefieldthat
willequipyouwiththetoolsandunderstandingtousestochasticlocalsearchtosolve
theproblemsyoucomeacross.’
TobyWalsh,CorkConstraintComputationCentre
UniversityCollegeCork
‘Thisbookprovidesremarkablecoverageandsynthesisoftherecentexplosionofwork
on randomized local search algorithms. It will serve as a good textbook for classes on
heuristic search and metaheuristics as well as a central reference for researchers. The
bookprovidesaunificationofabroadspectrumofmethodsthatenablesconcise,highly
readabledescriptionsoftheoreticalandexperimentalresults.’
DavidL.Woodruff,UniversityofCalifornia,Davis
Stochastic Local Search
Foundations and Applications
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Stochastic Local Search
Foundations and Applications
HolgerH.Hoos
DepartmentofComputerScience
UniversityofBritishColumbia
Canada
ThomasStützle
DepartmentofComputerScience
DarmstadtUniversityofTechnology
Germany
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