This book explores Multi-Criteria Decision Making (MCDM) methods, focusing on decision-making with multiple objectives and partial preference information. It integrates theoretical contributions with practical applications in areas such as energy, health systems, security, sustainability, industrial contexts, supplier selection, and more. The book highlights the use of mathematical programming, particularly linear programming, for analyzing alternatives with incomplete information on criteria weights.

A key feature of the book is its exploration of Decision Support Systems (DSS), including their evolution through behavioral experiments and neuroscience tools. It also covers Group Decision and Negotiation (GDN) with partial information, focusing on preference modeling in group settings.

Targeted at both practitioners and researchers, this book offers innovative insights into MCDM with partial information, making it an essential resource for those looking to improve their decision models or expand their knowledge in the field.

Introduces an innovative approach to decision-making, focusing on methods with multiple objectives Presents recent and ongoing developments in MCDM with partial information Covers a range of applications across various areas

Autorentext

Adiel Teixeira de Almeida is Full Professor at Universidade Federal de Pernambuco (UFPE), Brazil and holds a PhD in Management Engineering (Mgm Eng). His main research interest is in Multiple Criteria Decision Making (MCDM), Group Decision and Negotiation (GDN), Decision Support System (DSS) and Operational Research (OR). He has received the Georg Cantor Award from the International Society on MCDM and the INFORMS GDN Section Award. He is a Fellow of the International Federation of Operational Research Societies (IFORS) and the Brazilian Operational Research Society. He serves on the editorial board of several scholarly journals. He has served in the Executive Committee of the International Society on MCDM and as President of both the INFORMS MCDM Section and the INFORMS GDN Section.
Eduarda Asfora Frej is Assistant Professor at UFPE and holds a PhD in Mgm Eng. Her main research interest is in MCDM, GDN and DSS, in which she co-authored several journal papers. She is an active member of Societies on MCDM and GDN. She serves on the editorial board GDN Journal and as Editor of the GDN Newsletter. She has received the Junior Best Paper Award from the MCDM Section of INFORMS in 2021.
Lucia Reis Peixoto Roselli is Assistant Professor at UFPE and holds a PhD in Mgm Eng. Her main research interest is in MCDM, GDN, DSS and Decision Neuroscience, in which she co-authored several journal papers. She is an active member of Societies on MCDM, GDN and Neuroeconomics. She has received the Junior Best Paper Award from the MCDM Section of INFORMS in 2023.
Jônatas Araújo de Almeida is Associate Professor at UFPE and holds a PhD in Mgm Eng. He main research interests are in OR and MCDM, in which he co-authored several journal papers. He has received the Award for best Journal paper on Theory and Methodology in EJOR from EURO.
Ana Paula Cabral Seixas Costa is Full Professor at UFPE and holds a PhD in Mgm Eng. Her main research interest is in DSS, MCDM and GDN. She serves on the Editorial Board of the International Journal of Decision Support System Technology. She serves on the Board of the EWG-DSS. She has received the Award for best Journal paper on Theory and Methodology in EJOR.
Danielle Costa Morais is Full Professor at UFPE and holds PhD in Mgm Eng. Her main research interest is in MCDM, GDN and OR, in which she co-authored several journal papers. She serves on the editorial board of GDN Journal. She has served the board of the INFORMS MCDM section, the International Society of MCDM and GDN Section of INFORMS, being the VP of the latter.

Inhalt

General concepts on MCDM/A.- Preference modelling in MCDM.- Additive model for aggregation in the context of MAVT.- Basic Structure for Using Partial Preference Information in MCDM/A.- Methods Using Surrogate Weights.- Partial Preference Information Methods Exploring the Space of Weights.- Methods with non-compensatory preferences.- Decision Process with FITradeoff Method.- Theoretical foundation for FITradeoff Method.- FITradeoff for Choice Problematic.- FITradeoff for Ranking Problematic.- FITradeoff for Sorting Problematic.- FITradeoff for Portfolio Problematic.- DSS of the FITradeoff Method.- Applications Using FITradeoff Method.- Cases Using FITradeoff Method.- A Procedure for Replicating any problem solved with complete preference information.- Assessing the Readiness of Technology for Generating Energy.- FITradeoff for Group Decision.- FITradeoff Group Decision Support System.- Applications with FITradeoff for Group Decision.- FITradeoff for Negotiation.- FITradeoff Web-Based Platform for Negotiation.- Applications with FITradeoff for Negotiation.- Improving Methods with Behavioral and Decision Neuroscience.- Decision Neuroscience Studies for Preference Modeling.- Success-Based Decision Rule for Holistic Evaluation.- Inconsistency studies in the FITradeoff Method.