“To conclude this review, I recommend that departmental libraries buy this book for its presentation of state-of-the-art methodologies in multicriteria decision analysis as it relates to AI.” (Interfaces, 1 July 2015)
“This book covers a rich set of topics, including intelligent decision support technologies, data mining models for decision making, evidential reasoning, evolutionary multi-objective optimization, fuzzy modelling, as well as applications in management and engineering.” (Zentralblatt MATH 2016)
Presents recent advances in both models and systems for intelligent decision making
Organisations often face complex decisions requiring the assessment of large amounts of data. In recent years Multicriteria Decision Aid (MCDA) and Artificial Intelligence (AI) techniques have been applied with considerable success to support decision making in a wide range of complex real-world problems.
The integration of MCDA and AI provides new capabilities relating to the structuring of complex decision problems in static and distributed environments. These include the handling of massive data sets, the modelling of ill-structured information, the construction of advanced decision models, and the development of efficient computational optimization algorithms for problem solving. This book covers a rich set of topics, including intelligent decision support technologies, data mining models for decision making, evidential reasoning, evolutionary multiobjective optimization, fuzzy modelling, as well as applications in management and engineering.
Multicriteria Decision Aid and Artificial Intelligence:
- Covers all of the recent advances in intelligent decision making.
- Includes a presentation of hybrid models and algorithms for preference modelling and optimisation problems.
- Provides illustrations of new intelligent technologies and architectures for decision making in static and distributed environments.
- Explores the general topics on preference modelling and learning, along with the coverage of the main techniques and methodologies and applications.
- Written by experts in the field.
This book provides an excellent reference tool for the increasing number of researchers and practitioners interested in the integration of MCDA and AI for the development of effective hybrid decision support methodologies and systems. Academics and post-graduate students in the fields of operational research, artificial intelligence and management science or decision analysis will also find this book beneficial.
From the Back Cover
Presents recent advances in both models and systems for intelligent decision making
Organisations often face complex decisions requiring the assessment of large amounts of data. In recent years Multicriteria Decision Aid (MCDA) and Artificial Intelligence (AI) techniques have been applied with considerable success to support decision making in a wide range of complex real-world problems.
The integration of MCDA and AI provides new capabilities relating to the structuring of complex decision problems in static and distributed environments. These include the handling of massive data sets, the modelling of ill-structured information, the construction of advanced decision models, and the development of efficient computational optimization algorithms for problem solving. This book covers a rich set of topics, including intelligent decision support technologies, data mining models for decision making, evidential reasoning, evolutionary multiobjective optimization, fuzzy modelling, as well as applications in management and engineering.
Multicriteria Decision Aid and Artificial Intelligence:
- Covers all of the recent advances in intelligent decision making.
- Includes a presentation of hybrid models and algorithms for preference modelling and optimisation problems.
- Provides illustrations of new intelligent technologies and architectures for decision making in static and distributed environments.
- Explores the general topics on preference modelling and learning, along with the coverage of the main techniques and methodologies and applications.
- Written by experts in the field.
This book provides an excellent reference tool for the increasing number of researchers and practitioners interested in the integration of MCDA and AI for the development of effective hybrid decision support methodologies and systems. Academics and post-graduate students in the fields of operational research, artificial intelligence and management science or decision analysis will also find this book beneficial.
About the Author
Michael Doumpos, Technical University of Crete, Department of Production Engineering and Management, Greece.
Evangelos Grigoroudis, Technical University of Crete, Department of Production Engineering and Management, Greece.
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