Core Concepts
New heuristics improve MCS problem through Maximum Clique and Independent Set reformulation.
Abstract
The study introduces new heuristics to address the challenging Maximum Common Subgraph (MCS) problem by reformulating it as the Maximum Clique and its complement, the Maximum Independent Set. Leveraging the Motzkin-Straus theorem, replicator dynamics are used to optimize the Maximum Clique Problem. Annealed imitation heuristics are introduced to enhance convergence to better local optima. Additionally, strategies for the Maximum Independent Set problem are applied to efficiently reduce graph sizes, enabling faster computation and near-optimal solutions. The implementation of both techniques in a single algorithm shows promising results on Erd˝os-R´enyi graph pairs.
Stats
The study tested techniques on randomly generated Erd˝os-R´enyi graph pairs.
Results indicate potential application and impact on future research directions.
Quotes
"The study introduces new heuristics aimed at mitigating challenges in solving the MCS problem."
"Our techniques were tested on randomly generated Erd˝os-R´enyi graph pairs."