Optimal learning rate and neighborhood radius of Kohonen's self-organizing map for solving the travelling salesman problem
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Autor:in (Körperschaft)
Publikationsdatum
2018
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Proceedings of the 2nd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Reihennummer
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
54-59
Patentnummer
Verlag / Herausgebende Institution
Verlagsort / Veranstaltungsort
Phuket
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
The Travelling Salesman Problem (TSP) is one of the well-studied classic combinatorial optimization problems and proved to be a non-deterministic polynomial-time (NP) hard problem. Kohonen's self-organizing map (SOM) is a type of artificial neural network, which can be applied on the TSP. The purpose of the algorithm is to adapt a special network to a set of unorganized and unlabeled data so that it can be used for clustering and simple classification tasks. In this paper, we study the effect of changing the parameters in the SOM algorithm to solve the TSP. The focus of the parameter investigation lies on the influence of changes in the SOM learning rate and neighborhood radius as well as on the number of iterations in TSP problems with varying number of cities. Thus, the investigation is based on various problem instances as well as on different parameter settings of the SOM, which are compared with each other and discussed. The results are additionally compared with the nature inspired ant colony optimization (ACO) algorithm. As a result, it is proved that with the right parameter setting the SOM generated result is improved and that it is superior to the ACO algorithm.
Schlagwörter
Fachgebiet (DDC)
Veranstaltung
2nd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (ISMSI 2018)
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
24.03.2018
Enddatum der Konferenz
25.03.2018
Datum der letzten Prüfung
ISBN
978-1-4503-6412-6
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Closed
Lizenz
Zitation
Mersiovsky, T., Thekkottil, A., Hanne, T., & Dornberger, R. (2018). Optimal learning rate and neighborhood radius of Kohonen’s self-organizing map for solving the travelling salesman problem. Proceedings of the 2nd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence, 54–59. https://doi.org/10.1145/3206185.3206194