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.
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I. Introduction.- II. Basic Concepts and Foundations.- 1. Definitions.- 1.1 Terms for MCDM Environment.- 1.2 MCDM Solutions.- 2. Models for MADM.- 2.1 Noncompensatory Model.- 2.2 Compensatory Model.- 3. Transformation of Attributes.- 3.1 Quantification of Fuzzy Attributes.- 3.2 Normalization.- 4. Fuzzy Decision Rules.- 4.1 Definition of Fuzzy Set.- 4.2 Some Basic Operations of Fuzzy Sets.- 5. Methods for Assessing Weight.- 5.1 Eigenvector Method.- 5.2 Weighted Least Square Method.- 5.3 Entropy Method.- 5.4 Linmap.- III. Methods for Multiple Attribute Decision Making.- 1. Methods for No Preference Information Given.- 1.1.1 Dominance.- 1.1.2 Maximin.- 1.1.3 Maximax.- 2. Methods for Information on Attribute Given.- 2.1 Methods for Standard Level of Attribute Given.- 2.1.1 Conjunctive Method (Satisficing Method).- 2.1.2 Disjunctive Method.- 2.2 Methods for Ordinal Preference of Attribute Given.- 2.2.1 Lexicographic Method.- 2.2.2 Elimination By Aspects.- 2.2.3 Permutation Method.- 2.3 Methods for Cardinal Preference of Attribute Given.- 2.3.1 Linear Assignment Method.- 2.3.2 Simple Additive Weighting Method.- 2.3.3 Hierarchical Additive Weighting Method.- 2.3.4 ELECTRE Method.- 2.3.5 TOPSIS.- 2.4 Methods for Marginal Rate of Substitution of Attributes Given.- 2.4.1 Hierarchical Tradeoffs.- 3. Methods for Information on Alternative Given.- 3.1 Methods for Pairwise Preference Given.- 3.1.1 LINMAP.- 3.1.2 Interactive Simple Additive Weighting Method.- 3.2 Method for Pairwise Proximity Given.- 3.2.1 Multidimensional Scaling with Ideal Point.- IV. Applications.- 1. Commodity Selection.- 2. Facility Location (Siting) Selection.- 3. Personnel Selection.- 4. Project Selection.- 4.1 Environmental Planning.- 4.2 Land Use Planning.- 4.3 R & D Project.- 4.4 Water Resources Planning.- 4.5 Miscellaneous.- 5. Public Facility Selection.- V. Concluding Remarks.- On MADM Methods Classification.- On Applications of MADM.- On Multiple Objective Decision Making (MODM) Methods.- On Multiattribute Utility Theory (MAUT).- A Choice Rule for MADM Methods.- A Unified Approach to MADM.- On Future Study.- VI. Bibliography.- Books, Monographs, and Conference Proceedings.- Journal Articles, Technical Reports, and Theses.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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