Multi-Criteria and Multi-Dimensional Analysis in Decisions

Decision Making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM)

Specificaties
Gebonden, blz. | Engels
Springer Nature Switzerland | e druk, 2023
ISBN13: 9783031405372
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Juridisch :
Springer Nature Switzerland e druk, 2023 9783031405372
Onderdeel van serie Vector Optimization
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Samenvatting

A new era is emerging in which a group of quantitative methods featuring characteristics of multidimensional comparative analysis (MCA) and multi-criteria decision-making analysis (MCDA) can be used to automate objective decision-making processes. This book introduces the character of the criteria (desirable, non-desirable, motivating, demotivating, and neutral) to MCDA and MCA methods. It presents the author’s own developed methods, the preference vector method (PVM), for solving multi-criteria problems in decision making; and, vector measure construction method (VMCM), which is dedicated to solving typical problems in the field of multidimensional comparative analysis. All methods are explained step by step with relevant examples, primarily in the fields of economics and management.

Specificaties

ISBN13:9783031405372
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Switzerland

Inhoudsopgave

<p>Chapter 1 Introduction.- Chapter 2 Problems of multi-criteria and multidimensionality in decision support.- Part I: Methods of multidimensional comparative analysis.- Chapter 3 Initial data analysis procedure.- Chapter 4 Methods for building aggregate measures.- Part II: Multi-criteria decision support methods.- Chapter 5 Methods based on the outranking relationship.- Chapter 6 Methods based on the utility function.- Chapter 7 Multi-criteria methods using function points.- Chapter 8 Conclusions.</p>

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        Multi-Criteria and Multi-Dimensional Analysis in Decisions