Efficient Approximation and Online Algorithms : Recent Progress on Classical Combinatorial Optimization Problems and New Applications / edited by Evripidis Bampis, Klaus Jansen, Claire Kenyon.

Springer eBooks

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 Lovász-Local-Lemma and Scheduling.

This book provides a good opportunity for computer science practitioners and researchers to get in sync with the 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. This state-of-the-art survey contains 11 carefully selected papers that cover some classical problems of scheduling, of packing, and of graph theory, but also new optimization problems arising in various applications like networks, data mining or classification.

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