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November 8, 20250 citationsOpen Access

Finding a Shortest Curve that Separates Few Objects from Many

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TBThérèse BiedlÉVÉric Colin de VerdièreFFFabrizio Frati

Key Points

  • The proposed algorithm finds the shortest curve that encloses required polygons, separating them from unwanted objects.
  • Runtime complexity is established at O(3^kn^3) for n vertices across k required polygons.
  • The study extends to a graph context, minimizing edge weights with a focus on k required faces and their associated penalties.
  • FPT algorithms could enable solutions for NP-hard geometric challenges, contributing to areas like geometric knapsack.

Abstract

We present a fixed-parameter tractable (FPT) algorithm to find a shortest curve that encloses a set of k required objects in the plane while paying a penalty for enclosing unwanted objects. The input is a set of interior-disjoint simple polygons in the plane, where k of the polygons are required to be enclosed and the remaining optional polygons have non-negative penalties. The goal is to find a closed curve that is disjoint from the polygon interiors and encloses the k required polygons, while minimizing the length of the curve plus the penalties of the enclosed optional polygons. If the penalties are high, the output is a shortest curve that separates the required polygons from the others. The problem is NP-hard if k is not fixed, even in very special cases. The runtime of our algorithm is O (3ᵏn³), where n is the number of vertices of the input polygons. We extend the result to a graph version of the problem where the input is a connected plane graph with positive edge weights. There are k required faces; the remaining faces are optional and have non-negative penalties. The goal is to find a closed walk in the graph that encloses the k required faces, while minimizing the weight of the walk plus the penalties of the enclosed optional faces. We also consider an inverted version of the problem where the required objects must lie outside the curve. Our algorithms solve some other well-studied problems, such as geometric knapsack.

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Cite This Study

Biedl et al. (2025) studied this question.

synapsesocial.com/papers/690e8b75a5b062d7a4e737cbhttps://doi.org/10.4230/lipics.socg.2025.15
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