These proceedings include papers presented at the VII-th Internatio nal Conference on Multiple Criteria Decision Making which was held in Kyoto/Japan on August 18-22, 1986. Multiple Criteria Decision Making (MCDM) has been a greatly import ant subject in many practical fields, for example, in planning, design, control and management in both private and public sectors. After remark able developments of theory, methodology and pilot case studies in rec ent years, it is now facing the stage of real applications and develop ment of more sophisticated methodology as interactive intelligent decision support systems. The conference aimed to provide a significant contribu tion to the future of MCDM as one of total systems including human factors: Substantial emphasis was given to knowledge engineering and cognitive sci ence. The conference inherits the tradition and the style of the previous conferences: (1) Jouy-en-Josas/France (1975), (2) Buffalo/U.S.A. (1977), (3) Konigswinter/FRG (1978), (4) Delaware/U.S.A. (1980), (5) Mons/Belgium (1982), (6) Cleveland/U.S.A. (1984). This time a great many Japanese com panies provided grants for the conference. As a result, the total number of participants was over 120, and a computer demonstration could be reali zed on an extensive scale as well as the conference sessions. Throughout the conference, it was observed that MCDM is making steady progress not only in theory but also as a tool for decision support.

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.

In the past, technological as well as economic forces dominated the evolution of industrial structures: these factors have been treated extensively in numerous studies. However, another major factor which has begun to have a decisive influ ence on the performance of the chemical industry is technological risk and public and environmental health considerations, in particular those related to toxic and hazardous substances used in industrial production processes. The issues of con trolling process risk, waste streams, and potential environmental consequences of accidental or routine release of hazardous chemicals are rapidly gaining in impor tance vis CI vis narrow economic considerations, and are increasingly reflected in national and international legislation. In the context of several ongoing R&D projects aiming at the development of a new generation of tools for "intelligent" decision support, two related problem areas that have been identified are: (i) Structuring the industry or plant for the minimum cost of production as well as least risk - e.g., toxicity of chemicals involved. In this multi-criteria framework, we seek to resolve the conflict between industrial structure or plant design established by economic considerations and the one shaped by environmental concerns. This can be formulated as a design problem for nor mal production conditions. In section 3.1. and 3.2. an approach on how to deal with this problem at the industry and plant level is discussed.

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.

This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities for the practical use of biometric and intelligent decision making support.