Multiple Criteria Optimization
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Multiple Criteria Optimization
This text on operations research statistics is designed for junior and senior graduate courses in multiple criteria decision making, multiple criteria optimization, and multiple objective programming. The book shows how to implement the techniques of multiple criteria optimization for solving large-scale multiple objective problems on a computer. It contains full details on such recent breakthrough developments as the Tchebycheff method, a method that enables one to solve large-scale multiple objective linear, integer and nonlinear programming problems. Included are numerous exercises for solving problems manually and by using a computer.
Multiple Criteria Optimization
Author: Xavier Gandibleux
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-04-11
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 ”new wave” 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.
Multiple Criteria Decision Analysis: State of the Art Surveys
Author: Salvatore Greco
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-01-20
Multiple Criteria Decision Analysis: State of the Art Surveys provides survey articles and references of the seminal or state-of-the-art research on MCDA. The material covered ranges from the foundations of MCDA, over various MCDA methodologies (outranking methods, multiattribute utility and value theories, non-classical approaches) to multiobjective mathematical programming, MCDA applications, and software. This vast amount of material is organized in 8 parts, with a total of 25 chapters. More than 2000 references are listed.