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      Probability Theory and Combinatorial Optimization

      AvJ. Michael Steele

      Häftad, Engelska, 1997

      Del i serien CBMS-NSF Regional Conference Series in Applied Mathematics

      759 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      This monograph provides an introduction to the state of the art of the probability theory that is most directly applicable to combinatorial optimization. Much attention is paid to those questions dealing with discrete optimization problems for points in Euclidean space, such as the minimum spanning tree, the traveling-salesman tour, and minimal-length matchings. Still, there are several nongeometric optimization problems that receive full treatment, and these include the problems of the longest common subsequence and the longest increasing subsequence. The philosophy that guides the exposition is that analysis of concrete problems is the most effective way to explain even the most general methods or abstract principles.There are three fundamental probabilistic themes that are examined through our concrete investigations. First, there is a systematic exploitation of martingales. Over the last ten years, many investigators of problems of combinatorial optimization have come to count on martingale inequalities as versatile tools which let us show that many of the naturally occurring random variables of combinatorial optimization are sharply concentrated about their means - a phenomenon with numerous practical and theoretical consequences.The second theme that is explored is the systematic use of subadditivity of several flavors, ranging from the naïve subadditivity of real sequences to the subtler subadditivity of stochastic processes. By and large, subadditivity offers only elementary tools, but on remarkably many occasions such tools provide the key organizing principle in the attack on problems of nearly intractable difficulty.The third and deepest theme developed here concerns the application of Talagrand's isoperimetric theory of concentration inequalities. This new theory is reshaping almost everything that is known in the probability theory of combinatorial optimization. The treatment given here deals with only a small part of Talagrand's theory, but the reader will find considerable coaching on how to use some of the most important ideas from that theory.

      Produktinformation

      • Utgivningsdatum:1997-12-31
      • Mått:152 x 229 x 10 mm
      • Vikt:317 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:CBMS-NSF Regional Conference Series in Applied Mathematics
      • Antal sidor:167
      • Förlag:Society for Industrial & Applied Mathematics,U.S.
      • ISBN:9780898713800

      Utforska kategorier

      • Matematisk statistik inom Naturvetenskap och teknik
      • Kombinatorik och grafteori inom Naturvetenskap och teknik
      • Tillämpad matematik inom Naturvetenskap och teknik

      Innehållsförteckning

      • PrefaceChapter 1: First View of Problems and Methods. A first example: Long common subsequencesSubadditivity and expected valuesAzuma’s inequality and a first applicationA second example: The increasing-subsequence problemFlipping Azuma’s inequalityConcentration on ratesDynamic programmingKingman’s subadditive ergodic theoremObservations on subadditive subsequencesAdditional notesChapter 2: Concentration of Measure and the Classical Theorems. The TSP and quick application of Azuma’s inequalityEasy size boundsAnother mean PoissonizationThe Beardwood-Halton-Hammersly theoremKarp’s partitioning algorithmsIntroduction to space-filling curve heuristicAsymptotics for the space-filling curve heuristicAdditional notesChapter 3: More General Methods. Subadditive Euclidean functionalsExamples: Good, bad and forthcomingA general L-(infinity) boundSimple subadditivity and geometric subadditivityA concentration inequalityMinimal matchingTwo-sided bounds and first consequencesRooted duals and their applicationsLower bounds and best possibilitiesAdditional remarksChapter 4: Probability in Greedy Algorithms and Linear Programming. Assignment problemSimplex method for theoreticiansDyer-Frieze-McDiarmid inequalityDealing with integral constraintsDistributional boundsBack to the futureAdditional remarksChapter 5: Distributional Techniques and the Objective Method. Motivation for a methodSearching for a candidate objectTopology for nice setsInformation on the infinite treeDénoumentCentral limit theoryConditioning method for independenceDependency graphs and the CLTAdditional remarksChapter 6: Talagrand’s Isoperimetric Theory. Talagrand’s isoperimetric theoryTwo geometric applications of the isoperimetric inequalityApplication to the longest-increasing-subsequence problemProof of the isoperimetric problemApplication and comparison in the theory of hereditary setsSuprema of linear functionalsTail of the assignment problemFurther applications of Talagrand’s isoperimetric inequalitiesFinal considerations on related workBibliographyIndex.
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