Fuzzy Applications in Industrial Engineering

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Kahraman, Cengiz (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
• Σειρά: Studies in Fuzziness and Soft Computing, 201
• Θέματα: Engineering.; Information technology.; Business > Data processing.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Industrial engineering.; Production engineering.; Appl.Mathematics/Computational Methods of Engineering.; Industrial and Production Engineering.; Artificial Intelligence (incl. Robotics).; Applications of Mathematics.; IT in Business.

 Industrial Engineering (IE) is concerned with the design, improvement, and installation of integrated systems of people, material, equipment, and energy. Industrial engineers face many problems with incomplete and vague information in these systems since the characteristics of these problems often require this kind of information. Fuzzy sets approaches are usually most appropriate when human evaluations and the modeling of human knowledge are needed. IE brings a significant number of applications of fuzzy set theory. After an introductory chapter explaining the recent status of fuzzy sets in IE, this volume involves application chapters on the major seven areas of IE to which fuzzy set theory can contribute. These major application areas are Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and Ergonomics, Manufacturing Systems and Technology Management, Optimization Techniques, and Statistical Decision-making. Under these major areas, every chapter includes didactic numerical applications. 

 Applications of Fuzzy Sets in Industrial Engineering: A Topical Classification -- Applications of Fuzzy Sets in Industrial Engineering: A Topical Classification -- Fuzzy Control Techniques and Reliability in Industry -- Design of Fuzzy Process Control Charts for Linguistic and Imprecise Data -- Fuzzy Rule Reduction and Tuning of Fuzzy Logic Controllers for a HVAC System -- A Study of 3-gene Regulation Networks Using NK-Boolean Network Model and Fuzzy Logic Networking -- Optimizing Nuclear Reactor Operation Using Soft Computing Techniques -- Fuzzy Engineering Economics and Investment Analysis Techniques -- Applications of Fuzzy Capital Budgeting Techniques -- Fuzzy Capital Budgeting: Investment Project Evaluation and Optimization -- Option Pricing Theory in Financial Engineering from the Viewpoint of Fuzzy Logic -- Fuzzy Group and Multi-criteria Decision-making Techniques -- A Multi-granular Linguistic Hierarchical Model to Evaluate the Quality of Web Site Services -- Optimization and Decision Making under Interval and Fuzzy Uncertainty: Towards New Mathematical Foundations -- Interval Evaluations in DEA and AHP -- A General Form of Fuzzy Group Decision Making Choice Functions under Fuzzy Preference Relations and Fuzzy Majority -- Fuzzy Techniques in Human Factors Engineering and Ergonomics -- The Application of Neural Fuzzy Approaches to Modeling of Musculoskeletal Responses in Manual Lifting Tasks -- Intelligent Interfaces Based on Fuzzy Logic: Example with a Human-Error-Tolerant Interface Approach -- Estimation of Ease Allowance of a Garment using Fuzzy Logic -- Fuzzy Techniques in Manufacturing Systems and Technology Management -- Intelligent Manufacturing Management -- Metaheuristic Techniques for Job Shop Scheduling Problem and a Fuzzy Ant Colony Optimization Algorithm -- Fuzzy Techniques in Scheduling of Manufacturing Systems -- Fuzzy Optimization Techniques -- Fuzzy Cognitive Mapping for MIS Decision-Making -- Fuzzy Sets based Cooperative Heuristics for Solving Optimization Problems -- Solving a Fuzzy Nonlinear Optimization Problem by an “ad hoc” Multi-objective Evolutionary Algorithm -- Fuzzy Statistical Decision-making Techniques -- Multi Attribute Performance Evaluation Using a Hierarchical Fuzzy TOPSIS Method -- Fuzzy Quantitative Association Rules and Its Applications -- Fuzzy Regression Approaches and Applications.