Titlebook: Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques; Third International Dorit S. Hochbaum,Klaus Janse

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/r/image/821119.jpg

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https://doi.org/10.1007/b72324Approximation Algorithms; Combinatorial Approximation; Complexity; Randomization; Scheduling; algorithms;

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Multicoloring Planar Graphs and Partial?,-TreesWe study the multicoloring problem with two objective functions: minimizing the . and minimizing the .. We focus on partial?.-trees and planar graphs. In particular, we give polynomial time approximation schemes (PTAS) for both classes, for both preemptive and non-preemptive multisum colorings.

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Probabilistic and Deterministic Approximations of the PermanentThe exact computation of the permanent of a matrix is #.-complete. Many efforts have been made to efficiently approximate the permanent. In this talk we will survey some of these methods, both probabilistic and deterministic..The papers below and the references within them serve as a good source of information on this topic.

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Dorit S. Hochbaum,Klaus Jansen,Alistair SinclairIncludes supplementary material:

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Approximating Minimum Manhattan Networkst most 4. times that of a minimum Manhattan network. Using known rectangulation algorithms, this gives us an .(..)-time algorithm with approximation factor four, and an .(. log .)-time algorithm with approximation factor eight.

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Set Cover with Requirements and Costs Evolving over Timeecisely the above difficulty..The above extension of the set cover problem arose in a toolkit for automated design and architecture evolution of high speed networks. Further optimization problems that arise in the same context include survivable network design, facility location with demands and nat