This book provides a good opportunity for computer science practitioners and researchers to get in sync with current state-of-the-art and future trends in the field of combinatorial optimization and online algorithms. Recent advances in this area are presented focusing on the design of efficient approximation and on-line algorithms. One central idea in the book is to use a linear program relaxation of the problem, randomization and rounding techniques.

Contenuti:

Contributed Talks.- On Approximation Algorithms for Data Mining Applications.- A Survey of Approximation Results for Local Search Algorithms.- Approximation Algorithms for Path Coloring in Trees.- Approximation Algorithms for Edge-Disjoint Paths and Unsplittable Flow.- Independence and Coloring Problems on Intersection Graphs of Disks.- Approximation Algorithms for Min-Max and Max-Min Resource Sharing Problems, and Applications.- A Simpler Proof of Preemptive Total Flow Time Approximation on Parallel Machines.- Approximating a Class of Classification Problems.- List Scheduling in Order of ?-Points on a Single Machine.- Approximation Algorithms for the k-Median Problem.- The Lov�sz-Local-Lemma and Scheduling.

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Efficient Approximation and Online Algorithms: Recent Progress on Classical Combinatorial Optimization Problems and New Applications (Lecture Notes in Computer Science, 3484)

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