Multicriteria Decision Aid and Artificial Intelligence

Multicriteria Decision Aid and Artificial Intelligence
Author: Michael Doumpos
Publisher: John Wiley & Sons
Total Pages: 328
Release: 2013-02-01
Genre: Business & Economics
ISBN: 1118522494

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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. Is 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.

Intelligent Support Systems for Marketing Decisions

Intelligent Support Systems for Marketing Decisions
Author: Nikolaos F. Matsatsinis
Publisher: Springer Science & Business Media
Total Pages: 517
Release: 2012-12-06
Genre: Business & Economics
ISBN: 146151147X

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Intelligent Support Systems for Marketing Decisions examines new product development, market penetration strategies, and other marketing decisions utilizing a confluence of methods, including Decision Support Systems (DSS), Artificial Intelligence in Marketing and Multicriteria Analysis. The authors systematically examine the use and implementation of these methodologies in making strategic marketing decisions. Part I discusses the basic concepts of multicriteria analysis vis-à-vis marketing decisions and in new product development situations. Part II presents basic concepts from the fields of Information Systems, Decision Support Systems, and Intelligent Decision Support Methods. In addition, specialized categories of DSS (multicriteria DSS, web-based DSS, group DSS, spatial DSS) are discussed in terms of their key features and current use in marketing applications. Part III presents IDSS and a multicriteria methodology for new product development. Further chapters present a developmental strategy for analyzing, designing, and implementing an Intelligent Marketing Decision Support System. The implementation discussion is illustrated with a real-world example of the methods and system in use.

Multicriteria Decision Aid and Resource Management

Multicriteria Decision Aid and Resource Management
Author: Athanasios Spyridakos
Publisher: Springer Nature
Total Pages: 179
Release: 2023-08-16
Genre: Business & Economics
ISBN: 3031348923

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This book is focused on the application of methodological approaches and systems of multiple criteria decision analysis (MCDA) in the field of resource management. Resource management constitutes a major challenge of modern times. The book comprehensively examines cases of human resources, material resources and natural resources in particular. It focuses on the efficient utilization of these resources to achieve sustainability of economic, environmental and social aspects. Also, the book presents methodological tools which aim to support the decision making at operational, executive and strategic levels.The book presents recent results of scientific research in the field of MCDA and its applications to resource management. It investigates the resource management challenges and introduces innovative methodological approaches and systems for addressing these resources management issues.

Intelligent Decision Support Systems

Intelligent Decision Support Systems
Author: Miquel Sànchez-Marrè
Publisher: Springer Nature
Total Pages: 826
Release: 2022-03-28
Genre: Computers
ISBN: 3030877906

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This book, with invaluable contributions of Professor Franz Wotawa in chapters 5 and 7, presents the potential use and implementation of intelligent techniques in decision making processes involved in organizations and companies. It provides a thorough analysis of decisions, reviewing the classical decision theory, and describing usual methods for modeling the decision process. It describes the chronological evolution of Decision Support Systems (DSS) from early Management Information Systems until the appearance of Intelligent Decision Support Systems (IDSS). It explains the most commonly used intelligent techniques, both data-driven and model-driven, and illustrates the use of knowledge models in Decision Support through case studies. The author pays special attention to the whole Data Science process, which provides intelligent data-driven models in IDSS. The book describes main uncertainty models used in Artificial Intelligence to model inexactness; covers recommender systems; and reviews available development tools for inducing data-driven models, for using model-driven methods and for aiding the development of Intelligent Decision Support Systems.

Exploring Intelligent Decision Support Systems

Exploring Intelligent Decision Support Systems
Author: Rafael Valencia-García
Publisher: Springer
Total Pages: 252
Release: 2018-02-07
Genre: Technology & Engineering
ISBN: 3319740024

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This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.

Intelligent Decision-making Support Systems

Intelligent Decision-making Support Systems
Author: Jatinder N.D. Gupta
Publisher: Springer Science & Business Media
Total Pages: 508
Release: 2007-03-30
Genre: Technology & Engineering
ISBN: 1846282314

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This book will be bought by researchers and graduates students in Artificial Intelligence and management as well as practising managers and consultants interested in the application of IT and information systems in real business environment.

Intelligent Decision Support Systems

Intelligent Decision Support Systems
Author: Salvatore Greco
Publisher: Springer Nature
Total Pages: 446
Release: 2022-05-31
Genre: Business & Economics
ISBN: 3030963187

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This book presents a collection of essays written by leading researchers to honor Roman Słowiński’s major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding. The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.

Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare

Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
Author: Ilker Ozsahin
Publisher: Bentham Science Publishers
Total Pages: 316
Release: 2021-11-18
Genre: Computers
ISBN: 168108872X

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This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis). Key Features: - Introduces readers to the basics of AI and ML in expert systems for healthcare - Focuses on a problem solving approach to the topic - Provides information on relevant decision-making theory and data science used in the healthcare industry - Includes practical applications of AI and ML for advanced readers - Includes bibliographic references for further reading The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.

Intelligent Decision and Policy Making Support Systems

Intelligent Decision and Policy Making Support Systems
Author: Da Ruan
Publisher: Springer Science & Business Media
Total Pages: 320
Release: 2008-04-24
Genre: Computers
ISBN: 3540783067

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This edited book reports recent research results and provides a state-of-the-art on intelligent decision support systems applications, lessons learned and future research directions. The book covers a balanced mixture of theory and practice, including new methods and developments of intelligent decision support systems applications in Society and Policy Support. Its main objective is to gather a peer-reviewed collection of high quality contributions in the relevant topic areas.

Intelligent Strategies for Meta Multiple Criteria Decision Making

Intelligent Strategies for Meta Multiple Criteria Decision Making
Author: Thomas Hanne
Publisher: Springer Science & Business Media
Total Pages: 206
Release: 2012-12-06
Genre: Business & Economics
ISBN: 1461515955

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Multiple criteria decision-making research has developed rapidly and has become a main area of research for dealing with complex decision problems which require the consideration of multiple objectives or criteria. Over the past twenty years, numerous multiple criterion decision methods have been developed which are able to solve such problems. However, the selection of an appropriate method to solve a particular decision problem is today's problem for a decision support researcher and decision-maker. Intelligent Strategies for Meta Multiple Criteria Decision-Making deals centrally with the problem of the numerous MCDM methods that can be applied to a decision problem. The book refers to this as a `meta decision problem', and it is this problem that the book analyzes. The author provides two strategies to help the decision-makers select and design an appropriate approach to a complex decision problem. Either of these strategies can be designed into a decision support system itself. One strategy is to use machine learning to design an MCDM method. This is accomplished by applying intelligent techniques, namely neural networks as a structure for approximating functions and evolutionary algorithms as universal learning methods. The other strategy is based on solving the meta decision problem interactively by selecting or designing a method suitable to the specific problem, for example, the constructing of a method from building blocks. This strategy leads to a concept of MCDM networks. Examples of this approach for a decision support system explain the possibilities of applying the elaborated techniques and their mutual interplay. The techniques outlined in the book can be used by researchers, students, and industry practitioners to better model and select appropriate methods for solving complex, multi-objective decision problems.