Improving performance in combinatorial optimisation using averaging and clustering

Abstract

In a recent paper an algorithm for solving MAX-SAT was proposed which worked by clustering good solutions and restarting the search from the closest feasible solutions. This was shown to be an extremely effective search strategy, substantially out-performing traditional optimisation techniques. In this paper we extend those ideas to a second classic NP-Hard problem, namely Vertex Cover. Again the algorithm appears to provide an advantage over more established search algorithms, although it shows different characteristics to MAX-SAT.We argue this is due to the different large-scale landscape structure of the two problems. © Springer-Verlag Berlin Heidelberg 2009.