Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys

The generalized area of multiple criteria decision making (MCDM) can be defined as the body of methods and procedures by which the concern for multiple conflicting criteria can be formally incorporated into the analytical process. MCDM consists mostly of two branches, multiple criteria optimization...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Ehrgott, Matthias. (Editor), Gandibleux, Xavier. (Editor)
Format: Electronic
Language:English
Published: Boston, MA : Springer US, 2002.
Series:International Series in Operations Research & Management Science, 52
Subjects:
Online Access:View fulltext via EzAccess
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505 0 # |a Theory of Vector Optimization -- Nonlinear Multiobjective Programming -- Goal Programming in the Period 1990Ớ<U+001c>2000 -- Fuzzy Multiobjective and Multilevel Optimization -- Interactive Nonlinear Multiobjective Procedures -- Evolutionary Algorithms and Multiple Objective Optimization -- Data Envelopment Analysis in Multicriteria Decision Making -- Multiobjective Combinatorial Optimization Ớ Theory, Methodology, and Applications -- Multicriteria Scheduling Problems. 
520 # # |a The generalized area of multiple criteria decision making (MCDM) can be defined as the body of methods and procedures by which the concern for multiple conflicting criteria can be formally incorporated into the analytical process. MCDM consists mostly of two branches, multiple criteria optimization and multi-criteria decision analysis (MCDA). While MCDA is typically concerned with multiple criteria problems that have a small number of alternatives often in an environment of uncertainty (location of an airport, type of drug rehabilitation program), multiple criteria optimization is typically directed at problems formulated within a mathematical programming framework, but with a stack of objectives instead of just one (river basin management, engineering component design, product distribution). It is about the most modern treatment of multiple criteria optimization that this book is concerned. I look at this book as a nicely organized and well-rounded presentation of what I view as Ớ<U+00fd>new waveỚ<U+00fd> topics in multiple criteria optimization. Looking back to the origins of MCDM, most people agree that it was not until about the early 1970s that multiple criteria optimization c- gealed as a field. At this time, and for about the following fifteen years, the focus was on theories of multiple objective linear programming that subsume conventional (single criterion) linear programming, algorithms for characterizing the efficient set, theoretical vector-maximum dev- opments, and interactive procedures. 
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