Description: Non-Convex Multi-Objective Optimization, Hardcover by Pardalos, Panos M.; Žilinskas, Antanas; Žilinskas, Julius, ISBN 3319610058, ISBN-13 9783319610054, Brand New, Free shipping in the US Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.
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Book Title: Non-Convex Multi-Objective Optimization
Number of Pages: Xii, 192 Pages
Language: English
Publication Name: Non-Convex Multi-Objective Optimization
Publisher: Springer International Publishing A&G
Publication Year: 2017
Subject: Programming / Algorithms, Applied, Optimization
Item Weight: 152.4 Oz
Type: Textbook
Author: Julius ŽIlinskas, Panos M. Pardalos, Antanas ŽIlinskas
Subject Area: Mathematics, Computers
Item Length: 9.3 in
Series: Springer Optimization and Its Applications Ser.
Item Width: 6.1 in
Format: Hardcover
