A Handbook on Multi-Attribute Decision-Making Methods. Omid Bozorg-Haddad
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A Handbook on Multi‐Attribute Decision‐Making Methods
Omid Bozorg‐Haddad
University of Tehran
Alborz, Iran
Babak Zolghadr‐Asli
University of Tehran
Alborz, Iran
Hugo A. Loáiciga
University of California
Santa Barbara, United States
This edition first published 2021
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The right of Omid Bozorg‐Haddad, Babak Zolghadr‐Asli, and Hugo A. Loáiciga to be identified as the authors of this work has been asserted in accordance with law.
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Library of Congress Cataloging‐in‐Publication Data
Names: Bozorg-Haddad, Omid, 1974‐ author. | Zolghadr‐Asli, Babak, author. |
Loáiciga, Hugo A., author.
Title: A handbook on multi‐attribute decision‐making methods / Omid
Bozorg‐Haddad, Babak Zolghadr‐Asli, Hugo A. Loáiciga.
Description: Hoboken, NJ : Wiley, 2021. | Series: Wiley series in
operations research and management science | Includes bibliographical
references and index.
Identifiers: LCCN 2020034049 (print) | LCCN 2020034050 (ebook) | ISBN
9781119563495 (cloth) | ISBN 9781119563471 (adobe pdf) | ISBN
9781119563389 (epub) | ISBN 9781119563501 (obook)
Subjects: LCSH: Multiple criteria decision making.
Classification: LCC T57.95 .B69 2021 (print) | LCC T57.95 (ebook) | DDC
658.4/03–dc23
LC record available at https://lccn.loc.gov/2020034049
LC ebook record available at https://lccn.loc.gov/2020034050
Cover Design: Wiley
Cover Image: © connel/Shutterstock
Preface
Multi‐attribute decision‐making (MADM) problems describe a situation in which the decision‐makers evaluate a finite number of pre‐defined alternatives that are explicitly known at the beginning of the solution process with regard to a set of often conflictive evaluating criteria. It would not be an exaggeration to state that almost everyone, whether in their personal or professional life, faces decision‐making problems on a daily basis. Although there are numerous MADM methods at the decision‐makers’ disposal to cope with real‐world decision‐making problems there is still lacking a source that compiles and explains the various MADM methods in a clear and systematic manner that would make their understanding, comparison, and application straightforward for those who require