Approximation and Online Algorithms: 14th International Workshop, WAOA 2016, Aarhus, Denmark, August 25-26, 2016, Revised Selected Papers

by Klaus Jansen (Editor), Monaldo Mastrolilli (Editor)

Overview

This book constitutes the thoroughly refereed post-workshop proceedings of the 14th International Workshop on Approximation and Online Algorithms, WAOA 2016, held in Aarhus, Denmark, in August 2016 as part of ALGO 2016.
The 16 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 33 submissions. Topics of interest for WAOA 2016 were: coloring and partitioning, competitive analysis, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques, real world applications, and scheduling problems.

Product Details

ISBN-13:	9783319517407
Publisher:	Springer International Publishing
Publication date:	02/11/2017
Series:	Lecture Notes in Computer Science , #10138
Edition description:	1st ed. 2017
Pages:	211
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

Approximation Algorithms for the k-Set Packing Problem.- On Linear and Semidefinite Programs for Polytopes in Combinatorial Optimization.- The Shortest Separating Cycle Problem.- Dynamic Traveling Repair Problem with an Arbitrary Time Window.- A PTAS for the Cluster Editing Problem on Planar Graphs.- Bin Packing with Colocations.- Batch Coloring of Graphs.- New Integrality Gap Results for the Firefighters Problem on Trees.- A Multiplicative Weights Update Algorithm for Packing and Covering Semi-Infinite Linear Programs.- Balanced Optimization with Vector Costs.- Vertex Sparsification in Trees.- Scenario Submodular Cover.- Non-Greedy Online Steiner Trees on Outerplanar Graphs.- A Refined Analysis of Online Path Coloring in Trees.- Resource Allocation Games with Multiple Resource Classes.- Tight Approximation Bounds for the Seminar Assignment Problem.- A Priori TSP in the Scenario Model.- Local Search Based Approximation Algorithms for Two-Stage Shastic Location Problems.