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Nonlinear Assignment Problems (NAPs) are natural extensions of the
classic Linear Assignment Problem, and despite the efforts of many
researchers over the past three decades, they still remain some of
the hardest combinatorial optimization problems to solve exactly.
The purpose of this book is to provide in a single volume, major
algorithmic aspects and applications of NAPs as contributed by
leading international experts. The chapters included in this book
are concerned with major applications and the latest algorithmic
solution approaches for NAPs. Approximation algorithms, polyhedral
methods, semidefinite programming approaches and heuristic
procedures for NAPs are included, while applications of this
problem class in the areas of multiple-target tracking in the
context of military surveillance systems, of experimental high
energy physics, and of parallel processing are presented. Audience:
Researchers and graduate students in the areas of combinatorial
optimization, mathematical programming, operations research,
physics, and computer science.
Nonlinear Assignment Problems (NAPs) are natural extensions of the
classic Linear Assignment Problem, and despite the efforts of many
researchers over the past three decades, they still remain some of
the hardest combinatorial optimization problems to solve exactly.
The purpose of this book is to provide in a single volume, major
algorithmic aspects and applications of NAPs as contributed by
leading international experts. The chapters included in this book
are concerned with major applications and the latest algorithmic
solution approaches for NAPs. Approximation algorithms, polyhedral
methods, semidefinite programming approaches and heuristic
procedures for NAPs are included, while applications of this
problem class in the areas of multiple-target tracking in the
context of military surveillance systems, of experimental high
energy physics, and of parallel processing are presented. Audience:
Researchers and graduate students in the areas of combinatorial
optimization, mathematical programming, operations research,
physics, and computer science.
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