Applications of fuzzy set methodologies in industrial engineering
著者
書誌事項
Applications of fuzzy set methodologies in industrial engineering
(Advances in industrial engineering, v. 8)
Elsevier, 1989
大学図書館所蔵 全42件
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注記
Includes index
内容説明・目次
内容説明
Fuzzy set approaches always seem to be most appropriate when the modeling of human knowledge is necessary. This also happens when human evaluations are needed, in decision making, in project planning, in production control, in organizational design, and whenever interfaces between human users and computers have to be designed. Until recently these interfaces had to be implemented using digital hardware. Lately however, fuzzy chips and fuzzy computers have been developed; these will soon provide for efficient fuzzy on-line control. Industrial engineering is an area full of potential applications for fuzzy set theory. The appearance of this book marks the first introductory text of its kind dedicated to this area. The editors have combined contributions from world renowned experts on the various topics covered such as: traditional industrial engineering techniques; ergonomics; safety engineering; human performance measurement; man-machine systems and fuzzy methodologies. Accordingly, the book contains papers on the major areas of industrial engineering to which fuzzy set theory can contribute.
目次
I. Introduction. An introduction to fuzzy set methodologies for industrial and systems engineering (G.W. Evans et al.). Methodological and applicational aspects of fuzzy models for systems engineering (W. Pedrycz). II. Control of Industrial Processes. Fuzzy control of industrial processes (P.A.S. Ralston, T.L. Ward). A mathematical model and algorithm of fuzzy controller (Song Da-he). III. Traditional Industrial Engineering Functions. Fuzzy location problems (C.M. Klein, R.K. Kincaid). Fuzzy knowledge in an artificial intelligence system for job shop scheduling (D. Dubois). Fuzzy discounted cash flow analysis (T.L. Ward). Fuzzy PERT (J.J. Buckley). Network analysis of fuzzy technologies (M. Mares). A robust regression method of fuzzy data (M. Inuiguchi et al.). IV. Human Factors. Fuzzy modeling of risk factors for industrial accident prevention: some empirical results (W. Karwowski et al.). Fuzzy rational aggregation for mental load and fatigue assessment (T. Marek, C. Noworol). Fuzzy sets and phrase crafting: Designing instructions and warnings (N.R. Kodali, J.G. Kreifeldt). V. Organizational Design and Financial Management. Span of control and organizational design (S. Yeralan, C.M. Klein). Equipment life estimation using fuzzy set theory (J.H. Wang et al.). Cost variance investigation with fuzzy sets (T.W. Lin, D.E. O'Leary). VI. Operations Research and Decision Making. Multiple objective linear programming over a fuzzy feasible set (P. Korhonen et al.). Relationship between fuzzy set programming and semi-infinite linear programming (J.A. Pence, A.L. Soyster). Support development tools for rational decision-making systems design (A.F. Blishun). Linguistic quantifiers and fuzzy majorities for more realistic and human-consistent group decision models (J. Kacprzyk, H. Nurmi). VII. Miscellaneous Applications. A fuzzy approach to optimal metallurgical grade assignment (F.J. Vasko et al.). A prototype expert system for selecting MRP lot-sizing heuristics based on fuzzy demand patterns (C.H. Dagli, I. Sabuncuoglu). A fuzzy decision-making to resolve regional conflicts between industry and the environment (A. Bardossy et al.). A framework of the fuzzy linguistic approach to facilities location problem (A. Mital, W. Karwowski). Author index.
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