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Central Triangulation under Parallel Flip Operations: The CG:SHOP Challenge 2026

Oswin Aichholzer, Joseph Dorfer, Sándor P. Fekete, Phillip Keldenich, Peter Kramer, Stefan Schirra

Abstract

We give an overview of the 2026 Computational Geometry Challenge targeting the problem of finding a Central Triangulation under Parallel Flip Operations in triangulations of point sets. A flip is the parallel exchange of a set of edges in a triangulation with opposing diagonals of the convex quadrilaterals containing them. The challenge objective was, given a set of triangulations of a fixed point set, to determine a central triangulation with respect to parallel flip distances. More precisely, this asks for a triangulation that minimizes the sum of flip distances to all elements of the input

Central Triangulation under Parallel Flip Operations: The CG:SHOP Challenge 2026

Abstract

We give an overview of the 2026 Computational Geometry Challenge targeting the problem of finding a Central Triangulation under Parallel Flip Operations in triangulations of point sets. A flip is the parallel exchange of a set of edges in a triangulation with opposing diagonals of the convex quadrilaterals containing them. The challenge objective was, given a set of triangulations of a fixed point set, to determine a central triangulation with respect to parallel flip distances. More precisely, this asks for a triangulation that minimizes the sum of flip distances to all elements of the input
Paper Structure (13 sections, 6 figures, 2 tables)

This paper contains 13 sections, 6 figures, 2 tables.

Figures (6)

  • Figure 1: Illustrative examples of (a) sequential and (b) parallel flip operations.
  • Figure 2: Three triangulations $T_1,T_2,T_3$ and a central triangulation $C$ with objective value $7$.
  • Figure 3: An example random instance with 15.0 points and 4.0 triangulations for which a center is to be found.
  • Figure 4: An example woc instance with 45.0 points and 4.0 triangulations for which a center is to be found.
  • Figure 5: Mean ratio to the best solution for the top 5 teams, by instance class. A value of 1.0 means the team matched the best known solution on every instance in that class.
  • ...and 1 more figures