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Monte Carlo Methods in Fuzzy Optimization [electronic resource] /by James J. Buckley, Leonard J. Jowers.

by Buckley, James J [author.]; Jowers, Leonard J [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Fuzziness and Soft Computing: 222Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Description: online resource.ISBN: 9783540762904.Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)DDC classification: 519 Online resources: Click here to access online
Contents:
Fuzzy Sets -- Crisp Random Numbers and Vectors -- Random Fuzzy Numbers and Vectors -- Tests for Randomness -- Applications -- Fuzzy Monte Carlo Method -- Fully Fuzzified Linear Programming I -- Fully Fuzzified Linear Programming II -- Fuzzy Multiobjective LP -- Solving Fuzzy Equations -- Fuzzy Linear Regression I -- Univariate Fuzzy Nonlinear Regression -- Multivariate Nonlinear Regression -- Fuzzy Linear Regression II -- Fuzzy Two-Person Zero-Sum Games -- Fuzzy Queuing Models -- Unfinished Business -- Fuzzy Min-Cost Capacitated Network -- Fuzzy Shortest Path Problem -- Fuzzy Max-Flow Problem -- Inventory Control: Known Demand -- Inventory Control: Fuzzy Demand -- Inventory Control: Backordering -- Fuzzy Transportation Problem -- Fuzzy Integer Programming -- Fuzzy Dynamic Programming -- Fuzzy Project Scheduling/PERT -- Max/Min Fuzzy Function -- Summary, Conclusions, Future Research -- Summary, Conclusions, Future Research.
In: Springer eBooksSummary: 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.
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Fuzzy Sets -- Crisp Random Numbers and Vectors -- Random Fuzzy Numbers and Vectors -- Tests for Randomness -- Applications -- Fuzzy Monte Carlo Method -- Fully Fuzzified Linear Programming I -- Fully Fuzzified Linear Programming II -- Fuzzy Multiobjective LP -- Solving Fuzzy Equations -- Fuzzy Linear Regression I -- Univariate Fuzzy Nonlinear Regression -- Multivariate Nonlinear Regression -- Fuzzy Linear Regression II -- Fuzzy Two-Person Zero-Sum Games -- Fuzzy Queuing Models -- Unfinished Business -- Fuzzy Min-Cost Capacitated Network -- Fuzzy Shortest Path Problem -- Fuzzy Max-Flow Problem -- Inventory Control: Known Demand -- Inventory Control: Fuzzy Demand -- Inventory Control: Backordering -- Fuzzy Transportation Problem -- Fuzzy Integer Programming -- Fuzzy Dynamic Programming -- Fuzzy Project Scheduling/PERT -- Max/Min Fuzzy Function -- Summary, Conclusions, Future Research -- Summary, Conclusions, Future Research.

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.

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