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By Ashkan Aazami, Michael D. Stilp (auth.), Moses Charikar, Klaus Jansen, Omer Reingold, José D. P. Rolim (eds.)

This quantity includes the papers awarded on the tenth foreign Workshopon Approximation Algorithms for Combinatorial Optimization Problems(APPROX 2007) and the eleventh overseas Workshop on Randomization andComputation (RANDOM 2007), which happened simultaneously at PrincetonUniversity, on August 20–22, 2007. APPROX specializes in algorithmic and complexityissues surrounding the advance of effective approximate solutionsto computationally tricky difficulties.

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Extra resources for Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques: 10th International Workshop, APPROX 2007, and 11th International Workshop, RANDOM 2007, Princeton, NJ, USA, August 20-22, 2007. Proceedings

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LNCS, vol. 2719, pp. 145–156. Springer, Heidelberg (2003) 3. : The approximation gap for the metric facility location problem is not yet closed. Operations Research Letters (ORL) 35(3), 379–384 (2007) 4. : Improved combinatorial algorithms for facility location and k-median problems. In: Proc. of the 40th IEEE Symp. on Foundations of Computer Science (FOCS), pp. 378–388. IEEE Computer Society Press, Los Alamitos (1999) 5. : Improved approximation algorithms for uncapacitated facility location. In: Proc.

240–257 (2002) 16. : Approximation algorithms for facility location problems (Lecture Notes), Report No. pdf 17. : Approximating the two-level facility location problem via a quasi-greedy approach. Mathematical Programming, Ser. A 108, 159–176 (2006) Improved Approximation Algorithms for the Spanning Star Forest Problem Ning Chen1, , Roee Engelberg2, , C. il 1 Abstract. A star graph is a tree of diameter at most two. A star forest is a graph that consists of node-disjoint star graphs. In the spanning star forest problem, given an unweighted graph G, the objective is to find a star forest that contains all the vertices of G and has the maximum number of edges.

Dokl. 4 (1963) 10. : Budget optimization in searchbased advertising auctions. In: Proceedings of the 8th ACM Conference on Electronic Commerce, (to appear) 11. : A multiple-choice secretary problem with applications to online auctions. In: SODA, pp. 630–631 (2005) 12. : Average-case analysis of off-line and on-line knapsack problems. In: SODA, pp. 179–188 (1995) 13. : Stochastic on-line knapsack problems. Mathematical Programming 68, 73–104 (1995) 14. : Randomized Algorithms. Cambridge University Press, Cambridge (1995) 15.

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