Monte Carlo Methods in Fuzzy Optimization

ISBN-13: 9783642095160 / Angielski / Miękka / 2010 / 260 str.

James J. Buckley;Leonard J. Jowers

Opis

1. 1 Introduction The objective of this book is to introduce Monte Carlo methods to ?nd good approximate solutions to fuzzy optimization problems. Many crisp (nonfuzzy) optimization problems have algorithms to determine solutions. This is not true for fuzzy optimization. There are other things to discuss in fuzzy optimization, which we will do later onin the book, like? and

Recenzje

From the reviews:

"This timely research monograph is a very much needed compendium of recent developments in the methodologies and applications of Monte Carlo fuzzy optimization and fuzzy modeling. ... Overall the writing is lucid and well supported by convincing and highly motivating comments. ... All in all, this is a highly welcome publication which will undoubtedly appeal to the fuzzy set research community." (Witold Pedrycz, Zentralblatt MATH, Vol. 1148, 2008)

Spis treści

Part I: Introduction 1 Introduction 3 2 Fuzzy Sets 3 Crisp Random Numbers and Vectors 4 Random Fuzzy Numbers and Vectors 5 Tests for Randomness Part II: Applications 6 Fuzzy Monte Carlo Method 7 Fully Fuzzi¯ed Linear Programming I 8 Fully Fuzzi¯ed Linear Programming II 9 Fuzzy Multiobjective LP 10 Solving Fuzzy Equations 11 Fuzzy Linear Regression I 12 Univariate Fuzzy Nonlinear Regression 13 Multivariate Nonlinear Regression 14 Fuzzy Linear Regression II 15 Fuzzy Two-Person Zero-Sum Games 16 Fuzzy Queuing Models Part III: Unfinished Business 17 Fuzzy Min-Cost Capacitated Network 18 Fuzzy Shortest Path Problem 19 Fuzzy Max-Flow Problem 20 Inventory Control: Known Demand 21 Inventory Control: Fuzzy Demand 22 Inventory Control: Backordering 23 Fuzzy Transportation Problem 24 Fuzzy Integer Programming 25 Fuzzy Dynamic Programming 26 Fuzzy Project Scheduling/PERT 27 Max/Min Fuzzy Function Part IV: Summary, Conclusions, Future Research 28 Summary, Conclusions, Future Research

Blurb

This book is a concise and readable introduction to Monte Carlo methods to find good approximate solutions to fuzzy optimization problems. Various basic applications and illustrative examples are presented in an understandable way. The aim of the book is to convince the reader that Monte Carlo methods can be useful in generating approximate solutions to fuzzy optimization problems.