Parallelizable Evolutionary Dynamics Principles for Solving the Maximum Clique Problem

Marcello Pelillo, Immanuel M. Bomze

Abstract: An algorithm for approximately solving the maximum clique is presented which uses relaxation labeling neural network techniques, focusing on the continuous problem formulation: maximize a quadratic form over the standard simplex. We employ somewhat surprising connections of the latter problem with dynamic principles of evolutionary game theory, and give a detailed report on our numerical experiences with the method proposed.