Evaluation and Decision Models with Multiple Criteria: Stepping stones for the analyst / Edition 1

Evaluation and Decision Models with Multiple Criteria: Stepping stones for the analyst / Edition 1

ISBN-10:
1441940537
ISBN-13:
9781441940537
Pub. Date:
02/11/2011
Publisher:
Springer US
ISBN-10:
1441940537
ISBN-13:
9781441940537
Pub. Date:
02/11/2011
Publisher:
Springer US
Evaluation and Decision Models with Multiple Criteria: Stepping stones for the analyst / Edition 1

Evaluation and Decision Models with Multiple Criteria: Stepping stones for the analyst / Edition 1

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Overview

Formal decision and evaluation models are sets of explicit and well-defined rules to collect, assess, and process information in order to be able to make recommendations in decision and/or evaluation processes. They are so widespread that almost no one can pretend not to have used or suffered the consequences of one of them.

Our earlier companion volume, Evaluation and Decision Models, heavily criticised formal models but also argued that they could be useful. On the other hand, Evaluation and Decision Models with Multiple Criteria is a guide aimed at helping the analyst to choose a model and use it consistently. We propose a sound analysis of techniques and our presentation can be extended to most decision and evaluation models as a "decision aiding methodology".

This volume is intended for the enlightened practitioner, for anyone who uses decision or evaluation models—-for research or for applications—-and is willing to question his practice, to have a deeper understanding of what he does.


Product Details

ISBN-13: 9781441940537
Publisher: Springer US
Publication date: 02/11/2011
Series: International Series in Operations Research & Management Science , #86
Edition description: Softcover reprint of hardcover 1st ed. 2006
Pages: 445
Product dimensions: 6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

and Preview.- Problem Formulation and Structuring: The Decision Aiding Process.- Numbers and Preferences.- Aggregation-Overture.- Aggregation Procedures.- Multi-Dimensional Preference Models.- Making Recommendation.- Conclusion and Perspectives.
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