"The River Method"
Michelle Döring, Markus Brill, and Jobst Heitzig have presented a new voting algorithm called River, which is based on pairwise comparisons. River is a simplified variation of Tideman's ranked pairs method, is easy to explain and compute, and provides unambiguous, interpretable trees that justify the decision. Unlike many classical methods, River exhibits strong resistance and independence from Pareto-dominated alternatives.
“Cost-Free Neutrality for the River Method”
Michelle Döring, Jannes Malanowski, and Stefan Neubert demonstrate that the River voting algorithm can be computed efficiently even when using tiebreakers. They present a polynomial algorithm (FUN) that simulates all possible tiebreakers in a single pass, thus calculating winners along with their corresponding decision trees. The results highlight structural advantages of River over classical methods such as ranked pairs. Both papers will be presented at the AAAI conference on January 20-27th at Singapore.
"Optimal Approximations for the Requirement Cut Problem on Sparse Graph Classes"
Nadym Mallek and Kirill Simonov explore a fundamental problem, called the Requirement Cut problem. It is about how to split networks while meeting certain separation requirements. This task underlies many questions in communication, logistics, and infrastructure design. While this problem is generally very difficult, we identify new types of network structures where it becomes much more manageable. For these networks, we can compute solutions that are very close to the optimal ones efficiently. The paper will be presented at the SOFSEM conference on February 9-13th 2026 at Kraków, Poland.
