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.