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Multi-criteria and multi-dimensional...

Nermend, Kesra.

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Multi-criteria and multi-dimensional analysis in decisions = decision making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multi-criteria and multi-dimensional analysis in decisions/ by Kesra Nermend.
Reminder of title:	decision making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) /
Author:	Nermend, Kesra.
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	xvi, 354 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Multiple criteria decision making. -
Online resource:	https://doi.org/10.1007/978-3-031-40538-9
ISBN:	9783031405389

Multi-criteria and multi-dimensional analysis in decisions = decision making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) /
Nermend, Kesra.

Multi-criteria and multi-dimensional analysis in decisionsdecision making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) /[electronic resource] :by Kesra Nermend. - Cham :Springer Nature Switzerland :2023. - xvi, 354 p. :ill., digital ;24 cm. - Vector optimization,1867-898X. - Vector optimization..

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.

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.

ISBN: 9783031405389

Standard No.: 10.1007/978-3-031-40538-9doiSubjects--Topical Terms:

564005
Multiple criteria decision making.

LC Class. No.: HD30.23 / .N476 2023

Dewey Class. No.: 658.403

Multi-criteria and multi-dimensional analysis in decisions = decision making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) /
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505 0 $a 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.
520 $a 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.
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