Titlebook: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques; 10th International W Moses Charikar,Klaus Jansen,J

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Approximation Algorithms for the Max-Min Allocation Problemproximation algorithm for Max-Min when there are . people with subadditive utility functions. We also give a ./.-approximation algorithm (for . ≤ ./2) if the utility functions are additive and the utility of an item for a person is restricted to 0, 1 or . for some . > 1. The running time of this alg

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Hardness of Embedding Metric Spaces of Equal Sizeial time algorithm to approximate the minimum distortion within a factor of .((log.).) for any constant .> 0, unless .. We give a simple reduction from the . problem which was shown to be inapproximable by Chuzhoy and Naor [10].

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Maximum Gradient Embeddings and Monotone Clustering . ∈ ., . where . is a universal constant. Conversely we show that the above quadratic dependence on log. cannot be improved in general. Such embeddings, which we call ., yield a framework for the design of approximation algorithms for a wide range of clustering problems with monotone costs, includi

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Stanisław Dżułyński,Maria Sass-Gustkiewiczet of them online so as to maximize the total value. Such situations arise in many contexts, e.g., hiring workers, scheduling jobs, and bidding in sponsored search auctions..This problem, often called the ., is known to be inapproximable. Therefore, we make the enabling assumption that elements arri

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https://doi.org/10.1007/978-3-7091-4468-8s to obtain a new (1.6774,1.3738)- approximation algorithm for the UFL problem. Our linear programing rounding algorithm is the first one that touches the approximability limit curve . established by Jain et al. As a consequence, we obtain the first optimal approximation algorithm for instances domi