Abstract
The paper presents the Segment Based Approach (SBA) - a novel technique to solve the Traveling Salesman Problem. In this technique, the path is constructed from segments, which are sequences of adjacent edges. Although the approach is memory extensive, it has built-in measures for identifying useful segments and controlling its memory requirements. The paper contains a detailed description of the SBA operation and an analysis of the impact that its parameters have on the obtained results. The SBA has some advantages over solutions of the TSP that are inspired by Ant Colony System. It is capable of finding shorter paths than the ACO methods but its main advantage is low computational complexity and the superiority of SBA over the ACO grows with the increase of the distance matrice size. The parallelization of its operation is also possible in a more straightforward manner than in the case of the ACO.
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Siemiński, A. (2022). Segment Based Approach to Travelling Salesman Problem. In: Nguyen, N.T., Manolopoulos, Y., Chbeir, R., Kozierkiewicz, A., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2022. Lecture Notes in Computer Science(), vol 13501. Springer, Cham. https://doi.org/10.1007/978-3-031-16014-1_54
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DOI: https://doi.org/10.1007/978-3-031-16014-1_54
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