TY  - BOOK
AU  - 
AU  - 
ED  - SpringerLink (Online service)
TI  - Nonlinear Integer Programming
T2  - International Series in Operations Research & Management Science,
SN  - 9780387329956
AV  - QA402.5-402.6 
U1  - 519.6 23
PY  - 2006///
CY  - Boston, MA
PB  - Springer US
KW  - Mathematics
KW  - Computer science
KW  - Mathematical optimization
KW  - Operations research
KW  - Optimization
KW  - Operations Research/Decision Theory
KW  - Operations Research, Mathematical Programming
KW  - Mathematical Modeling and Industrial Mathematics
KW  - Mathematics of Computing
KW  - Math Applications in Computer Science
N1  - Optimality, Relaxation and General Solution Procedures -- Lagrangian Duality Theory -- Surrogate Duality Theory -- Nonlinear Lagrangian and Strong Duality -- Nonlinear Knapsack Problems -- Separable Integer Programming -- Nonlinear Integer Programming with a Quadratic Objective Function -- Nonseparable Integer Programming -- Unconstrained Polynomial 01 Optimization -- Constrained Polynomial 01 Programming -- Two Level Methods for Constrained Polynomial 01 Programming -- Mixed-Integer Nonlinear Programming -- Global Descent Methods; ZDB-2-SMA
N2  - It is not an exaggeration that much of what people devote in their hfe reá solves around optimization in one way or another. On one hand, many decision making problems in real applications naturally result in optimization problems in a form of integer programming. On the other hand, integer programming has been one of the great challenges for the optimization research community for many years, due to its computational difficulties: Exponential growth in its computational complexity with respect to the problem dimension. Since the pioneering work of R. Gomory [80] in the late 1950s, the theoretical and methodological development of integer programming has grown by leaps and bounds, mainly focusing on linear integer programming. The past few years have also witnessed certain promising theoretical and methodological achieveá ments in nonlinear integer programming. When the first author of this book was working on duality theory for n- convex continuous optimization in the middle of 1990s, Prof. Douglas J. White suggested that he explore an extension of his research results to integer proá gramming. The two authors of the book started their collaborative work on integer programming and global optimization in 1997. The more they have investigated in nonlinear integer programming, the more they need to further delve into the subject. Both authors have been greatly enjoying working in this exciting and challenging field
UR  - http://dx.doi.org/10.1007/0-387-32995-1
ER  -