Approximate Covering with Lower and Upper Bounds via LP Rounding

07/22/2020
by   Sayan Bandyapadhyay, et al.
0

In this paper, we study the lower- and upper-bounded covering (LUC) problem, where we are given a set P of n points, a collection ℬ of balls, and parameters L and U. The goal is to find a minimum-sized subset ℬ'⊆ℬ and an assignment of the points in P to ℬ', such that each point p∈ P is assigned to a ball that contains p and for each ball B_i∈ℬ', at least L and at most U points are assigned to B_i. We obtain an LP rounding based constant approximation for LUC by violating the lower and upper bound constraints by small constant factors and expanding the balls by again a small constant factor. Similar results were known before for covering problems with only the upper bound constraint. We also show that with only the lower bound constraint, the above result can be obtained without any lower bound violation. Covering problems have close connections with facility location problems. We note that the known constant-approximation for the corresponding lower- and upper-bounded facility location problem, violates the lower and upper bound constraints by a constant factor.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/22/2020

Improved Bounds for Metric Capacitated Covering Problems

In the Metric Capacitated Covering (MCC) problem, given a set of balls ℬ...
research
08/02/2021

Efficient covering of convex domains by congruent discs

In this paper, we consider the problem of covering a plane region with u...
research
09/04/2017

Extending the small-ball method

The small-ball method was introduced as a way of obtaining a high probab...
research
12/20/2021

Quasi-uniform designs with optimal and near-optimal uniformity constant

A design is a collection of distinct points in a given set X, which is a...
research
02/14/2012

Lipschitz Parametrization of Probabilistic Graphical Models

We show that the log-likelihood of several probabilistic graphical model...
research
11/23/2020

Ordinary differential equations (ODE): metric entropy and nonasymptotic theory for noisy function fitting

This paper establishes novel results on the metric entropy of ODE soluti...
research
07/15/2011

From Small-World Networks to Comparison-Based Search

The problem of content search through comparisons has recently received ...

Please sign up or login with your details

Forgot password? Click here to reset