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For a long time the techniques of solving linear optimization (LP)
problems improved only marginally. Fifteen years ago, however, a
revolutionary discovery changed everything. A new golden age' for
optimization started, which is continuing up to the current time.
What is the cause of the excitement? Techniques of linear
programming formed previously an isolated body of knowledge. Then
suddenly a tunnel was built linking it with a rich and promising
land, part of which was already cultivated, part of which was
completely unexplored. These revolutionary new techniques are now
applied to solve conic linear problems. This makes it possible to
model and solve large classes of essentially nonlinear optimization
problems as efficiently as LP problems. This volume gives an
overview of the latest developments of such High Performance
Optimization Techniques'. The first part is a thorough treatment of
interior point methods for semidefinite programming problems. The
second part reviews today's most exciting research topics and
results in the area of convex optimization. Audience: This volume
is for graduate students and researchers who are interested in
modern optimization techniques.
For a long time the techniques of solving linear optimization (LP)
problems improved only marginally. Fifteen years ago, however, a
revolutionary discovery changed everything. A new `golden age' for
optimization started, which is continuing up to the current time.
What is the cause of the excitement? Techniques of linear
programming formed previously an isolated body of knowledge. Then
suddenly a tunnel was built linking it with a rich and promising
land, part of which was already cultivated, part of which was
completely unexplored. These revolutionary new techniques are now
applied to solve conic linear problems. This makes it possible to
model and solve large classes of essentially nonlinear optimization
problems as efficiently as LP problems. This volume gives an
overview of the latest developments of such `High Performance
Optimization Techniques'. The first part is a thorough treatment of
interior point methods for semidefinite programming problems. The
second part reviews today's most exciting research topics and
results in the area of convex optimization. Audience: This volume
is for graduate students and researchers who are interested in
modern optimization techniques.
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