Managing In Uncertainty Theory And Practice
Download and Read Managing In Uncertainty Theory And Practice full books in PDF, ePUB, and Kindle. Read online free Managing In Uncertainty Theory And Practice ebook anywhere anytime directly on your device. We cannot guarantee that every ebooks is available!
Managing in Uncertainty: Theory and Practice
Author | : Constantin Zopounidis |
Publisher | : Springer Science & Business Media |
Total Pages | : 520 |
Release | : 2013-04-17 |
Genre | : Business & Economics |
ISBN | : 147572845X |
Download Managing in Uncertainty: Theory and Practice Book in PDF, Epub and Kindle
This book provides a new point of view on the subject of the management of uncertainty. It covers a wide variety of both theoretical and practical issues involving the analysis and management of uncertainty in the fields of finance, management and marketing. Audience: Researchers and professionals from operations research, management science and economics.
Managing in Uncertainty: Theory and Practice Related Books
Language: en
Pages: 520
Pages: 520
Type: BOOK - Published: 2013-04-17 - Publisher: Springer Science & Business Media
This book provides a new point of view on the subject of the management of uncertainty. It covers a wide variety of both theoretical and practical issues involv
Language: en
Pages:
Pages:
Type: BOOK - Published: 1985 - Publisher:
Language: en
Pages: 395
Pages: 395
Type: BOOK - Published: 2015-11-13 - Publisher: MIT Press
A comprehensive framework for assessing strategies for managing risk and uncertainty, integrating theory and practice and synthesizing insights from many fields
Language: en
Pages: 408
Pages: 408
Type: BOOK - Published: 2019-04-04 - Publisher: Springer
This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It ex
Language: en
Pages: 205
Pages: 205
Type: BOOK - Published: 2008-12-28 - Publisher: Springer
Real-life decisions are usually made in the state of uncertainty such as randomness and fuzziness. How do we model optimization problems in uncertain environmen