© 1998

Probabilistic Methods for Algorithmic Discrete Mathematics

  • Michel Habib
  • Colin McDiarmid
  • Jorge Ramirez-Alfonsin
  • Bruce Reed


  • Probabilistic methods belong to the hottest topics in combinatorics and the theory of algorithms


Part of the Algorithms and Combinatorics book series (AC, volume 16)

Table of contents

  1. Front Matter
    Pages I-XVII
  2. Michael Molloy
    Pages 1-35
  3. Alan M. Frieze, Bruce Reed
    Pages 36-92
  4. Rajeev Motwani, Prabhakar Raghavan
    Pages 93-115
  5. Colin McDiarmid
    Pages 195-248
  6. Back Matter
    Pages 315-325

About this book


The book gives an accessible account of modern pro- babilistic methods for analyzing combinatorial structures and algorithms. Each topic is approached in a didactic manner but the most recent developments are linked to the basic ma- terial. Extensive lists of references and a detailed index will make this a useful guide for graduate students and researchers. Special features included:
- a simple treatment of Talagrand inequalities and their applications
- an overview and many carefully worked out examples of the probabilistic analysis of combinatorial algorithms
- a discussion of the "exact simulation" algorithm (in the context of Markov Chain Monte Carlo Methods)
- a general method for finding asymptotically optimal or near optimal graph colouring, showing how the probabilistic method may be fine-tuned to explit the structure of the underlying graph
- a succinct treatment of randomized algorithms and derandomization techniques


Graph Monte Carlo Method Probabilistic method Sim algorithm algorithms calculus probabilistic combinatorics randomized algorithms

Editors and affiliations

  • Michel Habib
    • 1
  • Colin McDiarmid
    • 2
  • Jorge Ramirez-Alfonsin
    • 3
  • Bruce Reed
    • 3
  1. 1.LIRMMMontpellier Cedex 5France
  2. 2.Department of StatisticsUniversity of OxfordOxfordUK
  3. 3.Equipe CombinatoireUniversité Pierre et Marie Curie, Paris 6 Case 189Paris Cedex 5France

Bibliographic information

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