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arXiv · 1810.08059

k-RNN: Extending NN-heuristics for the TSP

Nikolas Klug·Alok Chauhan·Ramesh Ragala·V Vijayakumar
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Abstract

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.

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Nikolas Klug, Alok Chauhan, Ramesh Ragala, V Vijayakumar. 2018-10-17. k-RNN: Extending NN-heuristics for the TSP. https://arxiv.org/abs/1810.08059

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