Abstract
The Minimum Routing Cost Spanning Tree problem is an optimization problem that strongly benefits from local search. Well-established approaches are the Ahuja-Murty local search and a weaker subtree search used in an evolutionary framework. We present a new and efficient cycle search that has a lower time complexity but achieves the same results as the strong but slow Ahuja-Murty local search. Moreover, we show that an evolutionary framework using this cycle search outperforms previous approaches regarding both quality and time. Our approach is able to find (near-)optimal solutions in all runs for all tested instances.
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Wolf, S., Merz, P. (2010). Efficient Cycle Search for the Minimum Routing Cost Spanning Tree Problem. In: Cowling, P., Merz, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2010. Lecture Notes in Computer Science, vol 6022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12139-5_24
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DOI: https://doi.org/10.1007/978-3-642-12139-5_24
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