Improved Approximation Bounds for the Minimum Constraint Removal Problem

Authors Sayan Bandyapadhyay, Neeraj Kumar, Subhash Suri, Kasturi Varadarajan

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Author Details

Sayan Bandyapadhyay
  • Department of Computer Science, University of Iowa, Iowa City, USA
Neeraj Kumar
  • Department of Computer Science, University of California, Santa Barbara, USA
Subhash Suri
  • Department of Computer Science, University of California, Santa Barbara, USA
Kasturi Varadarajan
  • Department of Computer Science, University of Iowa, Iowa City, USA

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Sayan Bandyapadhyay, Neeraj Kumar, Subhash Suri, and Kasturi Varadarajan. Improved Approximation Bounds for the Minimum Constraint Removal Problem. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 116, pp. 2:1-2:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


In the minimum constraint removal problem, we are given a set of geometric objects as obstacles in the plane, and we want to find the minimum number of obstacles that must be removed to reach a target point t from the source point s by an obstacle-free path. The problem is known to be intractable, and (perhaps surprisingly) no sub-linear approximations are known even for simple obstacles such as rectangles and disks. The main result of our paper is a new approximation technique that gives O(sqrt{n})-approximation for rectangles, disks as well as rectilinear polygons. The technique also gives O(sqrt{n})-approximation for the minimum color path problem in graphs. We also present some inapproximability results for the geometric constraint removal problem.

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
  • Minimum Constraint Removal
  • Minimum Color Path
  • Barrier Resilience
  • Obstacle Removal
  • Obstacle Free Path
  • Approximation


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