Marko Milenkovic

dblp:346/5566 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Computational geometry · 33% Automated reasoning and model checking · 33% Mathematical optimization · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Mathematical optimization › combinatorial optimization
local search
1.012026
ETH Flippers Approach to Parallel Reconfiguration of Triangulations: SAT Formulation and Heuristics (CG Challenge) · SoCG 2026
Automated reasoning and model checking › satisfiability
SAT encoding
1.012026
ETH Flippers Approach to Parallel Reconfiguration of Triangulations: SAT Formulation and Heuristics (CG Challenge) · SoCG 2026
Computational geometry
triangulation
1.012026
ETH Flippers Approach to Parallel Reconfiguration of Triangulations: SAT Formulation and Heuristics (CG Challenge) · SoCG 2026

Methods — techniques the papers use, named apart from their topics

greedy local search · 1.0edge coloring · 1.0SAT solving · 1.0
YearPublicationVenuePosition
2026 ETH Flippers Approach to Parallel Reconfiguration of Triangulations: SAT Formulation and Heuristics (CG Challenge)
abstract
We describe the algorithms used by the ETH Flippers team in the CG:SHOP 2026 Challenge. Each instance consists of a set of triangulations on a common point set, and the objective is to find a central triangulation that minimizes the total parallel flip distance to the input set. Our strategy combines an exact solver for small and medium-sized instances with a suite of heuristics for larger instances. For the exact approach, we formulate the problem as a SAT instance with XOR clauses to model edge transitions across multiple rounds, further optimized by lower bounds derived from exact pairwise distances. For larger instances, we use a greedy local search and edge-coloring techniques to identify maximal sets of independent flips. Our approach ranked second overall and first in the junior category, computing provably optimal solutions for 186 out of 250 instances.
Lorenzo Battini, Marko Milenkovic
SoCG2