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Fuzzy Probabilities and Fuzzy Sets for Web Planning

  • Book
  • © 2004

Overview

Authors:
  1. James J. Buckley

    1. Mathematics Department, University of Alabama at Birmingham, Birmingham, USA

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  • Offers state of the art in web planning with fuzzy methods

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 135)

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Table of contents (19 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Introduction

    • James J. Buckley
    Pages 1-4

  3. Fuzzy Sets

    • James J. Buckley
    Pages 5-20

  4. Fuzzy Probabilities/Arrival Rates

    • James J. Buckley
    Pages 21-34

  5. Fuzzy Markov Chains

    • James J. Buckley
    Pages 35-43

  6. Fuzzy Queuing Theory

    • James J. Buckley
    Pages 45-46

  7. Computations: One Sever

    • James J. Buckley
    Pages 47-52

  8. Example: One Sever

    • James J. Buckley
    Pages 53-57

  9. Computations: Two Servers

    • James J. Buckley
    Pages 59-61

  10. Example: Two Servers

    • James J. Buckley
    Pages 63-66

  11. Computations: Three or More Servers

    • James J. Buckley
    Pages 67-68

  12. Fuzzy Arrival/Service Rates

    • James J. Buckley
    Pages 69-71

  13. Example: Fuzzy Arrival/Service Rates

    • James J. Buckley
    Pages 73-81

  14. Optimization: Without Revenue/Costs

    • James J. Buckley
    Pages 83-110

  15. Optimization: With Revenue/Costs

    • James J. Buckley
    Pages 111-130

  16. Burstiness

    • James J. Buckley
    Pages 131-145

  17. Long Tailed Distributions

    • James J. Buckley
    Pages 147-159

  18. Putting It All Together

    • James J. Buckley
    Pages 161-169

  19. Summary and Future Research

    • James J. Buckley
    Pages 171-173

  20. Computational Algorithms

    • James J. Buckley
    Pages 175-180
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Keywords

About this book

1.1 Introduction This book is written in five major divisions. The first part is the introduc­ tory chapters consisting of Chapters 1-3. In part two, Chapters 4-10, we use fuzzy probabilities to model a fuzzy queuing system . We switch to employ­ ing fuzzy arrival rates and fuzzy service rates to model the fuzzy queuing system in part three in Chapters 11 and 12. Optimization models comprise part four in Chapters 13-17. The final part has a brief summary and sug­ gestions for future research in Chapter 18, and a summary of our numerical methods for calculating fuzzy probabilities, values of objective functions in fuzzy optimization, etc., is in Chapter 19. First we need to be familiar with fuzzy sets. All you need to know about fuzzy sets for this book comprises Chapter 2. Two other items relating to fuzzy sets, needed in Chapters 13-17, are also in Chapter 2: (1) how we plan to handle the maximum/minimum of a fuzzy set; and (2) how we will rank a finite collection of fuzzy numbers from smallest to largest.

Authors and Affiliations

  • Mathematics Department, University of Alabama at Birmingham, Birmingham, USA

    James J. Buckley

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