Monte Carlo Methods in Fuzzy Optimization

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.

Klappentext

Monte Carlo Methods in Fuzzy Optimization is a clear and didactic book about Monte Carlo methods using random fuzzy numbers to obtain approximate solutions to fuzzy optimization problems. The book includes various solved problems such as fuzzy linear programming, fuzzy regression, fuzzy inventory control, fuzzy game theory, and fuzzy queuing theory. The book will appeal to engineers, researchers, and students in Fuzziness and applied mathematics.

Inhalt

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