Multiobjective Optimization Interactive and Evolutionary Approaches
by
 
Branke, Jürgen. editor.

Title
Multiobjective Optimization Interactive and Evolutionary Approaches

Author
Branke, Jürgen. editor.

ISBN
9783540889083

Physical Description
online resource.

Series
Lecture Notes in Computer Science, 5252

Contents
Basics on Multiobjective Optimization -- to Multiobjective Optimization: Noninteractive Approaches -- to Multiobjective Optimization: Interactive Approaches -- to Evolutionary Multiobjective Optimization -- Recent Interactive and Preference-Based Approaches -- Interactive Multiobjective Optimization Using a Set of Additive Value Functions -- Dominance-Based Rough Set Approach to Interactive Multiobjective Optimization -- Consideration of Partial User Preferences in Evolutionary Multiobjective Optimization -- Interactive Multiobjective Evolutionary Algorithms -- Visualization of Solutions -- Visualization in the Multiple Objective Decision-Making Framework -- Visualizing the Pareto Frontier -- Modelling, Implementation and Applications -- Meta-Modeling in Multiobjective Optimization -- Real-World Applications of Multiobjective Optimization -- Multiobjective Optimization Software -- Parallel Approaches for Multiobjective Optimization -- Quality Assessment, Learning, and Future Challenges -- Quality Assessment of Pareto Set Approximations -- Interactive Multiobjective Optimization from a Learning Perspective -- Future Challenges.

Abstract
Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.

Subject Term
Computer science.
 
Computer software.
 
Electronic data processing.
 
Computational complexity.
 
Computation by Abstract Devices.
 
Algorithm Analysis and Problem Complexity.
 
Numeric Computing.
 
Discrete Mathematics in Computer Science.

Added Author
Branke, Jürgen.
 
Deb, Kalyanmoy.
 
Miettinen, Kaisa.
 
Słowiński, Roman.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
http://dx.doi.org/10.1007/978-3-540-88908-3


LibraryMaterial TypeItem BarcodeShelf NumberStatus
IYTE LibraryE-Book503788-1001QA75.5 -76.95Online Springer