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.
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Qasem, M., Prügel-Bennett, A. (2009). Improving Performance in Combinatorial Optimisation Using Averaging and Clustering. In: Cotta, C., Cowling, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2009. Lecture Notes in Computer Science, vol 5482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01009-5_16
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DOI: https://doi.org/10.1007/978-3-642-01009-5_16
Publisher Name: Springer, Berlin, Heidelberg
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