(Ebook PDF) Multiple Criteria Optimization State of the Art Annotated Bibliographic Surveys 1st edition by Xavier Gandibleux ISBN 0306481073 9780306481079 Full chapter

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ISBN 10:           0306481073
ISBN 13: 978-0306481079
Author:          Xavier Gandibleux

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 Optimization State of the Art Annotated Bibliographic Surveys 1st Table of contents:

Nonlinear Multiobjective Programming
An approach to optimization problems with multiple conflicting objectives, where the objective functions are nonlinear, requiring advanced mathematical methods for solving.

Goal Programming in the Period 1990–2000
A method used for multiobjective decision-making, focusing on achieving specific goals or targets, and how it evolved in the 1990s and early 2000s.

Fuzzy Multiobjective and Multilevel Optimization
Techniques involving fuzzy logic to handle uncertainty and imprecision in multiobjective optimization problems, including multi-level hierarchical decision processes.

Interactive Nonlinear Multiobjective Procedures
Methods that involve interaction between the decision-maker and the optimization algorithm to explore trade-offs between different objectives, especially in nonlinear contexts.

Evolutionary Algorithms and Multiple Objective Optimization
The use of evolutionary algorithms, such as genetic algorithms, to tackle multiobjective optimization problems by simulating natural selection processes to find optimal solutions.

Data Envelopment Analysis in Multicriteria Decision Making
A non-parametric method used to evaluate the efficiency of decision-making units (DMUs) in multiobjective decision-making settings, providing insight into performance relative to multiple criteria.

Multiobjective Combinatorial Optimization — Theory, Methodology, and Applications
The study of combinatorial problems (such as optimization in network design or scheduling) that involve multiple objectives, exploring both theoretical aspects and practical methodologies.

Multicriteria Scheduling Problems
The challenges and techniques in scheduling where multiple conflicting objectives (such as time, cost, or resource usage) need to be optimized simultaneously.

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