© 1998

Probabilistic Methods for Algorithmic Discrete Mathematics

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

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