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Approximation Algorithms for Network...
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Li, Shi.
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Approximation Algorithms for Network Routing and Facility Location Problems.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Approximation Algorithms for Network Routing and Facility Location Problems./
作者:
Li, Shi.
面頁冊數:
157 p.
附註:
Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
Contained By:
Dissertation Abstracts International75-04B(E).
標題:
Computer Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3608331
ISBN:
9781303663703
Approximation Algorithms for Network Routing and Facility Location Problems.
Li, Shi.
Approximation Algorithms for Network Routing and Facility Location Problems.
- 157 p.
Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
Thesis (Ph.D.)--Princeton University, 2014.
We study approximation algorithms for two classes of optimization problems.
ISBN: 9781303663703Subjects--Topical Terms:
626642
Computer Science.
Approximation Algorithms for Network Routing and Facility Location Problems.
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Source: Dissertation Abstracts International, Volume: 75-04(E), Section: B.
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Adviser: Moses Charikar.
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Thesis (Ph.D.)--Princeton University, 2014.
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We study approximation algorithms for two classes of optimization problems.
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The first class is network routing problems. These are an important class of optimization problems, among which the edge-disjoint paths (EDP ) problem is one of the central and most extensively studied. In the first part of my thesis, I will give a poly-logarithmic approximation for EDP with congestion 2. This culminates a long line of research on the EDP with congestion problem.
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The second class is facility location problems. Two important problems in this class are uncapacitated facility location (UFL) and k-median, both having long histories and numerous applications. We give improved approximation ratios for both problems in the second part of my thesis.
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For UFL, we present a 1.488-approximation algorithm for the metric uncapacitated facility location (UFL) problem. The previous best algorithm, due to Byrka, gave a 1.5-approximation for UFL. His algorithm is parametrized by gamma whose value is set to a fixed number. We show that if gamma is randomly selected, the approximation ratio can be improved to 1.488.
520
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For k-median, we present an improved approximation algorithm for k-median. Our algorithm, which gives a 1+ 3 + epsilon-approximation for k-median, is based on two rather surprising components. First, we show that it suffices to find an alpha-approximate solution that contains k+ O(1) medians. Second, we give such a pseudo-approximation algorithm with alpha =1+ 3 + epsilon.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3608331
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