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Approximation and Complexity in Numerical Optimization - Continuous and Discrete Problems (Hardcover, 2000 ed.)
Loot Price: R5,781
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Approximation and Complexity in Numerical Optimization - Continuous and Discrete Problems (Hardcover, 2000 ed.)
Series: Nonconvex Optimization and Its Applications, 42
Expected to ship within 10 - 15 working days
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There has been much recent progress in approximation algorithms for
nonconvex continuous and discrete problems from both a theoretical
and a practical perspective. In discrete (or combinatorial)
optimization many approaches have been developed recently that link
the discrete universe to the continuous universe through geomet
ric, analytic, and algebraic techniques. Such techniques include
global optimization formulations, semidefinite programming, and
spectral theory. As a result new ap proximate algorithms have been
discovered and many new computational approaches have been
developed. Similarly, for many continuous nonconvex optimization
prob lems, new approximate algorithms have been developed based on
semidefinite pro gramming and new randomization techniques. On the
other hand, computational complexity, originating from the
interactions between computer science and numeri cal optimization,
is one of the major theories that have revolutionized the approach
to solving optimization problems and to analyzing their intrinsic
difficulty. The main focus of complexity is the study of whether
existing algorithms are efficient for the solution of problems, and
which problems are likely to be tractable. The quest for developing
efficient algorithms leads also to elegant general approaches for
solving optimization problems, and reveals surprising connections
among problems and their solutions. A conference on Approximation
and Complexity in Numerical Optimization: Con tinuous and Discrete
Problems was held during February 28 to March 2, 1999 at the Center
for Applied Optimization of the University of Florida."
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