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k-RNN: Extending NN-heuristics for the TSP
Published in Springer Science and Business Media LLC
Volume: 24
Issue: 4
Pages: 1210 - 1213
In this paper we present an extension of existing Nearest-Neighbor heuristics to an algorithm called k-Repetitive-Nearest-Neighbor. The idea is to start with a tour of k nodes and then perform a Nearest-Neighbor search from there on. After doing this for all permutations of k nodes the result gets selected as the shortest tour found. Experimental results show that for 2-RNN the solutions quality remains relatively stable between about 10% to 40% above the optimum. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
About the journal
JournalData powered by TypesetMobile Networks and Applications
PublisherData powered by TypesetSpringer Science and Business Media LLC
Open AccessYes