Optimization on Low Rank Nonconvex Structures [electronic resource] /

Global optimization is one of the fastest developing fields in mathematical optimization. In fact, an increasing number of remarkably efficient deterministic algorithms have been proposed in the last ten years for solving several classes of large scale specially structured problems encountered in such areas as chemical engineering, financial engineering, location and network optimization, production and inventory control, engineering design, computational geometry, and multi-objective and multi-level optimization. These new developments motivated the authors to write a new book devoted to global optimization problems with special structures. Most of these problems, though highly nonconvex, can be characterized by the property that they reduce to convex minimization problems when some of the variables are fixed. A number of recently developed algorithms have been proved surprisingly efficient for handling typical classes of problems exhibiting such structures, namely low rank nonconvex structures. Audience: The book will serve as a fundamental reference book for all those who are interested in mathematical optimization.

Bibliographic Details

Main Authors:	Konno, Hiroshi. author., Thach, Phan Thien. author., Tuy, Hoang. author., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Boston, MA : Springer US : Imprint: Springer, 1997
Subjects:	Mathematics., Operations research., Decision making., Convex geometry., Discrete geometry., Mathematical optimization., Management science., Optimization., Operation Research/Decision Theory., Operations Research, Management Science., Convex and Discrete Geometry.,
Online Access:	http://dx.doi.org/10.1007/978-1-4615-4098-4
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