Ching-Lai Hwang – författare

Optimal Reliability Design, first published in 2000, provides a detailed introduction to systems reliability and reliability optimization. Techniques for maximizing system reliability are described, focusing on component reliability enhancement and redundancy arrangement. The authors present several case studies and show how optimization techniques are applied in practice. They also pay particular attention to finding methods that give the optimal trade-off between reliability and cost. The book begins with a review of key background material, and a discussion of a range of optimization models. The authors go on to cover optimization tools, such as heuristics, discrete optimization, nonlinear programming, mixed integer programming, optimal arrangement, and metaheuristic algorithms. They also describe the computational implementation of these tools. Many numerical examples are included, and the book contains over 180 homework exercises. It is suitable as a textbook for graduate-level courses in reliability engineering and operations research. It will also be a valuable reference for practising engineers.

Optimal Reliability Design, first published in 2000, provides a detailed introduction to systems reliability and reliability optimization. Techniques for maximizing system reliability are described, focusing on component reliability enhancement and redundancy arrangement. The authors present several case studies and show how optimization techniques are applied in practice. They also pay particular attention to finding methods that give the optimal trade-off between reliability and cost. The book begins with a review of key background material, and a discussion of a range of optimization models. The authors go on to cover optimization tools, such as heuristics, discrete optimization, nonlinear programming, mixed integer programming, optimal arrangement, and metaheuristic algorithms. They also describe the computational implementation of these tools. Many numerical examples are included, and the book contains over 180 homework exercises. It is suitable as a textbook for graduate-level courses in reliability engineering and operations research. It will also be a valuable reference for practising engineers.

Multiple attribute decision making (MADM) procedures, a process for making preference decisions over the available alternatives which are characterized by multiple (usually conflicting) attributes are useful for improving decision making in a wide range of circumstances--from professional to managerial to political. Using real-world case examples, the authors introduce the reader to normative (for optimal decisions) MADM models. Beginning in chapter 2 with and introductions to the various attributes in a decision, the authors explore how MADM methods can be used for descriptive purposes to model the existing decision-making process, noncompensatory and scoring methods, accommodation of soft data, construction of a multiple decision support system, and the validity of methods. The authors also include a presentation of the advanced procedures of TOPSIS and ELECTRE. This manual offers social scientists an encapsulated view of MADM methods, their characteristics, applicability, and the methods for solving MADM problems.

This mono graph is intended for an advanced undergraduate or graduate course as weIl as for the researchers who want a compilation of developments in this rapidly growing field of operations research. This is a sequel to our previous work entitled "Multiple Objective Decision Making--Methods and Applications: A State-of-the-Art Survey," (No. 164 of the Lecture Notes). The literature on methods and applications of Multiple Attribute Decision Making (MADM) has been reviewed and classified systematically. This study provides readers with a capsule look into the existing methods, their char­ acteristics, and applicability to analysis of MADM problems. The basic MADM concepts are defined and a standard notation is introduced in Part 11. Also introduced are foundations such as models for MADM, trans­ formation of attributes, fuzzy decision rules, and methods for assessing weight. A system of classifying seventeen major MADM methods is presented. These methods have been proposed by researchers in diversified disciplines; half of them are classical ones, but the other half have appeared recently. The basic concept, the computational procedure, and the characteristics of each of these methods are presented concisely in Part 111. The computational procedure of each method is illustrated by solving a simple numerical example. Part IV of the survey deals with the applications of these MADM methods.

This monograph is intended for an advanced undergraduate or graduate course of engineering and management science. as well as for persons in business. industry. military or in any field. who want an introductory and a capsule look into the methods of group decision making under multiple criteria. This is a sequel to our previous works entitled "Multiple Objective Decision Making--Methods and Applications (No. 164 of the Lecture Notes). and "Multiple Attribute Decision Making--Methods and Applications (No. 186 of the Lecture Notes). Moving from a single decision maker (the consideration of Lecture Notes 164 and 186) to a multiple decision maker setting introduces a great deal of complexity into the analysis. The problem is no longer the selection of the most preferred alternative among the nondominated solutions according to one individual's (single decision maker's) preference structure. The analysis is extended to account for the conflicts among different interest groups who have different objectives. goals. and so forth. Group decision making under multiple criteria includes such diverse and interconnected fields as preference analysis. utility theory. social choice theory. committee decision theory. theory of voting. game theory. expert evaluation analysis. aggregation of qualitative factors. economic equilibrium theory. etc; these are simplified and systematically classified for beginners. This work is to provide readers with a capsule look into the existing methods. their characteristics. and applicability in the complexity of group decision making.

This monograph is intended for graduate courses in engineering and management science, as well as readers who want an introduction to the theories and methologies of Multiple Attribute Decision Making (MADM) in a fuzzy environment. Classical MADM introduces a great deal of complexity to the decision analysis. In a fuzzy environment, the decision analysis is extended to consider not only the aggregation of performance scores (which are fuzzy) but also the comparison of fuzzy numbers which cannot be easily compared as in the case of real numbers. Chapter 2 gives an overview of classical MADM. Chapter 3 presents the basic concepts and the mathematical operations of fuzzy set theory with figures and simple numerical examples in an easy-to-read and easy-to-follow manner. Chapter 4 deals with fuzzy ranking methods, which are widely used in many fuzzy applications (especially fuzzy optimization procedure). A systematic classification of nearly two dozen existing ranking methods is presented, and a system for classifying over one dozen fuzzy MADM methods is presented.The concept, algorithm and the characteristics of each method are discussed, and the computational procedure of each method is illustrated by solving a simple numerical example.

In the last 25 years, fuzzy set theory has been applied in many disciplines such as operations research, management science, control theory and artificial intelligence/expert systems. In this volume, methods and applications of fuzzy mathematical programming are first systematically and thoroughly reviewed and classified. The survey provides readers with a capsule look into the existing methods, and their characteristics and applicability to the analysis of fuzzy and possibilistic programming problems. To realize practical fuzzy modelling, solutions for real-world problems are presented, including production/manufacturing, transportation, assignment, games, environmental management, resource allocation, project investment, banking/finance, and agricultural economics. To improve the flexibility and robustness of fuzzy mathematical programming techniques, the expert decision-making support system IFLP is presented, which considers and solves all possibilities of a specific domain of (fuzzy) linear programming problems. Basic fuzzy set theories, membership functions, fuzzy decisions, operators and fuzzy arithmetic are introduced with simple numerical examples.An updated bibliographical listing of 60 books and about 300 papers, reports and theses is given.