Sequential Approximate Multiobjective Optimization Using Computational Intelligence [electronic resource] / by Min Yoon, Yeboon Yun, Hirotaka Nakayama.
By: Yoon, Min [author.]
Contributor(s): Yun, Yeboon [author.] | Nakayama, Hirotaka [author.] | SpringerLink (Online service)
Material type:
Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|
![]() |
e-Library
Electronic Book@IST |
EBook | Available |
Basic Concepts of Multi-objective Optimization -- Interactive Programming Methods for Multi-objective Optimization -- Generation of Pareto Frontier by Genetic Algorithms -- Multi-objective Optimization and Computational Intelligence -- Sequential Approximate Optimization -- Combining Aspiration Level Approach and SAMO -- Engineering Applications.
This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential approximate optimization based on metamodels is an effective tool from a practical viewpoint. Several sophisticated methods for sequential approximate multiobjective optimization using computational intelligence are introduced along with real applications, mainly engineering problems, in this book.
There are no comments for this item.