Work

A folding preprocess for the max k-cut problem

Year: 2025

Type: article

Abstract: Given graph $$G=(V,E)$$ G = ( V , E ) with vertex set V and edge set E, the max k-cut problem seeks to partition the vertex set V into at most k subsets that maximize the weight (number) of edges with endpoints in different parts. This paper proposes a graph folding procedure (i.e., a procedure that reduces the number of the vertices and edges of graph G) for the weighted max k-cut problem that may help reduce the problem’s dimensionality. While our theoretical results hold for any $$k \ge 2$$ k ≥ 2 , our computational results show the effectiveness of the proposed preprocess only for $$k=2$$ k = 2 and on two sets of instances. Furthermore, we observe that the preprocess improves the performance of a MIP solver on a set of large-scale instances of the max cut problem.

Source: Optimization Letters

DOI: 10.1007/s11590-025-02199-0

Authors: Ramin Fakhimi, Hamidreza Validi, Illya V. Hicks, Tamás Terlaky, Luis F. Zuluaga

Institutions: Lehigh University, Texas Tech University, Rice University

Language: English

Topic: Complexity and Algorithms in Graphs

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,090