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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) (Vector Optimization) by Kesra Nermend is a nonfiction available to read on EtoBox.

What is Multi-Criteria and Multi-Dimensional Analysis in Decisions: Decision Making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) (Vector Optimization) about?

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.

Who reads Multi-Criteria and Multi-Dimensional Analysis in Decisions: Decision Making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM) (Vector Optimization)?

Author

Kesra Nermend

Publisher

Springer International Publishing

Published

2023

Language

EN

ISBN

9783031405372

Category

nonfiction

Subjects

Business, Management, Technology