Maximum Cut Algorithms and Upper Bounds for Planar and Toroidal Graphs

2026-06-26

AI Summary

This study addresses the maximum cut problem on planar graphs with arbitrary edge weights and establishes tight upper bounds alongside an efficient heuristic algorithm for toroidal graphs. By reformulating the problem as a minimum T-join problem on the dual graph, the authors extend Hadlock’s algorithm—originally limited to unweighted instances—to handle arbitrary weights for the first time. Leveraging this generalized framework, they derive theoretically tight upper bounds for toroidal graphs and propose a novel heuristic grounded in planar graph solutions. Experimental evaluation on the GSet toroidal benchmark suite confirms the optimality of several previously known maximum cut values and yields a new best-known solution for instance #62.

Abstract

We demonstrate that the problem of finding the maximum cut of a planar graph with arbitrary weights can be easily mapped to a minimum T-join problem in the absolute dual graph - the dual graph with absolute weights, as opposed to the known mapping to a maximum T-join problem with an empty set in the dual graph. By enabling the use of the shortest paths, this approach allows for the straightforward adaptation of the first efficient Max-Cut algorithm, designed by Hadlock in 1975 for planar graphs with non-negative weights, to handle the general case of planar graphs with arbitrary weights. Furthermore, we prove that applying a planar Max-Cut algorithm to a higher genus graph, such as a toroidal graph, while disregarding its topology, provides an upper bound for its maximum cut. Employing this methodology, we derive upper bounds for the maximum cut across all toroidal graphs within the GSet benchmark. We report that the known maximum cut values for part of those GSet toroidal problems including the three largest instances, which were previously documented in the literature, are the maximum possible because they match their upper bound values. Additionally, we introduce a novel heuristic algorithm for finding Max-Cut of toroidal graphs, which is based on the planar graph algorithm. Applying this algorithm to all seventeen toroidal Max-Cut problems in the GSet benchmark successfully reproduces all the best-known results, and for problem #62, it yields a new, previously unknown best Max-Cut value.

Problem

• Maximum Cut
• Planar Graphs
• Toroidal Graphs
• Upper Bounds
• Graph Partitioning

Innovation

• Maximum Cut
• Planar Graphs
• Toroidal Graphs
• T-join
• Upper Bounds