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Permanent link (DOI): https://doi.org/10.7939/R3VH49

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Approximation Algorithms for Single-Minded Pricing and Unique Coverage on Graphs and Geometric Objects Open Access

Descriptions

Other title
Subject/Keyword
Tollbooth Problem
Approximation Algorithms
Unique Coverage
Randomized Algorithms
Highway Problem
Envy-Free Pricing
Single-Minded Pricing
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Khankhajeh, Seyed Sina
Supervisor and department
Salavatipour, Mohammad R.
Examining committee member and department
Friggstad, Zachary
Salavatipour, Mohammad R.
Stewart, Lorna
Department
Department of Computing Science
Specialization

Date accepted
2015-04-01T11:52:05Z
Graduation date
2015-06
Degree
Master of Science
Degree level
Master's
Abstract
We study the Single-Minded Pricing, Unique Coverage, and Uniform-Budget Single-Minded Pricing problems on graphs and on geometric objects. In Single Minded Pricing, we are given a set of items and a collection of subsets of the items, called demands. For each demand, we are also given a budget. If the sum of the prices of the items in a demand is less than or equal to the budget of that demand, then the contribution of that demand to the total revenue will be the sum of the prices of the items in that demand and zero otherwise. In this problem, we want to assign prices to the items in order to maximize the total revenue. Uniform-Budget Single-Minded Pricing is a special case of Single-Minded Pricing where the budgets for all the demands are equal. In Unique Coverage, given a set of elements and a collection of subsets of the elements, we want to find a subcollection of the subsets in order to maximize the number of the elements that are uniquely covered. These problems can be studied in different settings, such as on graphs or on geometric objects. When studied on graphs, the items or the elements are the edges of a given graph and the demands or the subsets are paths in the graph, and when studied on geometric objects, the items or the elements are given as points on a two dimensional plane and the demands or the subset as geometric objects on the plane. We introduce approximation algorithms for Single-Minded Pricing, Unique Coverage, and Uniform-Budget Single-Minded Pricing on different geometric objects such as rectangles and squares and on different graphs such as trees. We also prove different hardness results for these problems.
Language
English
DOI
doi:10.7939/R3VH49
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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