Multiobjective Optimization Interactive and Evolutionary Approaches /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Branke, Jürgen (Επιμελητής έκδοσης), Deb, Kalyanmoy (Επιμελητής έκδοσης), Miettinen, Kaisa (Επιμελητής έκδοσης), Słowiński, Roman (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Lecture Notes in Computer Science, 5252
• Θέματα: Computer science.; Computer programming.; Computers.; Algorithms.; Numerical analysis.; Computer science > Mathematics.; Computer Science.; Programming Techniques.; Computation by Abstract Devices.; Algorithm Analysis and Problem Complexity.; Numeric Computing.; Discrete Mathematics in Computer Science.

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 challen...

Πίνακας περιεχομένων:

• 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.