
Decision-Making Management
A Tutorial and Applications
Academic Press
Published on 21. July 2017
Book
Paperback/Softback
148 pages
978-0-12-811540-4 (ISBN)
Description
Decision-Making Management: A Tutorial and Applications provides practical guidance for researchers seeking to optimizing business-critical decisions employing Logical Decision Trees thus saving time and money. The book focuses on decision-making and resource allocation across and between the manufacturing, product design and logistical functions. It demonstrates key results for each sector with diverse real-world case studies drawn primarily from EU projects. Theory is accompanied by relevant analysis techniques, with a progressional approach building from simple theory to complex and dynamic decisions with multiple data points, including big data and lot of data. Binary Decision Diagrams are presented as the operating approach for evaluating large Logical Decision Trees, helping readers identify Boolean equations for quantitative analysis of multifaceted problem sets. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support analysis of multi-criteria decision-making problems with defined constraints and requirements. The final objective is to optimize dynamic decisions with original approaches employing useful tools, including Big Data analysis. Extensive annexes provide useful supplementary information for readers to follow methods contained in the book.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
Graduate students and professionals across business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying decision-making analysis, or who are required to solve large, specific and complex multi-criteria decision-making problems as part of their jobs. The work will also be of interest to industrial engineers and engineering designers working with optimization problems, but this is not the main audience.
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 152 mm
Width: 227 mm
Thickness: 11 mm
Weight
320 gr
ISBN-13
978-0-12-811540-4 (9780128115404)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Alberto Pliego Marugan | Fausto Pedro Garcia Marquez
Decision-Making Management
A Tutorial and Applications
E-Book
07/2017
Academic Press
€91.95
Available for download
Persons
Dr. Alberto Pliego Marugan holds a doctorate (cum laude) in Industrial Engineering at the University of Castilla-la Mancha (UCLM, Spain), with international mention. He is the main author of several works related to machine learning, optimization algorithms, maintenance management, and decision-making in industry. He worked at Everis and he is currently a PostDoc member of the Ingenium Research Group at UCLM. Fausto Pedro Garcia Marquez works as a Professor and as Director of the Ingenium Research Group at the Universidad De Castilla-La Mancha, Spain. He is an Honorary Senior Research Fellow at Birmingham University, UK, and a Lecturer at the Postgraduate European Institute. He has published more than 150 papers and 31 books (Elsevier, Springer, Pearson, McGraw-Hill, Intech, IGI, Marcombo, AlfaOmega). He has been Principal Investigator in 4 European projects, 6 national projects, and more than 150 projects for universities, companies, and other institutions. His main interests are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, and Data Science.
Author
Consultant for Everis Spain and Ingenium groups
Professor, Universidad De Castilla-La Mancha, Spain
Content
1. Introduction2. Logical Decision Tree Analysis3. Binary Decision Diagrams4. Case Studies5. LDT: Dynamic Analysis6. Decision-Making Optimization