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The website of Coburg University of Applied Sciences was translated using translation software provided by a third-party provider such as DeepL. The official text is the German version of the website. No liability is assumed, either explicitly or implicitly, for the accuracy, reliability, or correctness of the translations into another language.

Traveling Santa Problem: Optimization of a Million-Households Tour Within One Hour

Finding the shortest tour visiting all given points at least ones belongs to the most famous optimization problems until today (TSP . . . travelling salesman problem). Optimal solutions exist for many problems up to several ten thousand points. The major difficulty in solving larger problems is the required computational complexity. This shifts the research from finding the optimum with no time limitation to approaches that find good but sub-optimal solutions in pre-defined limited time. This paper proposes a new approach for two-dimensional symmetric problems with more than a million coordinates that is able to create good initial tours within few minutes. It is based on a hierarchical clustering strategy and supports parallel processing. In addition, a method is proposed that can correct unfavourable paths with moderate computational complexity. The new approach is superior to state-of-the-art methods when applied to TSP instances with non-uniformly distributed coordinates.

Titel:

Traveling Santa Problem: Optimization of a Million-Households Tour Within One Hour

Veröffentlichungsdatum:

12.04.2021

Publikationsart:

Zeitschriftenbeiträge

Forschungsschwerpunkt:

Medien:

Frontiers in Robotics and AI, 8:652417,

DOI:

https://doi.org/10.3389/frobt.2021.652417

Weblink:

Heft:

Band:

8

Artikelnummer:

ISBN:

Autoren:

Tilo Strutz

Medien:

Frontiers in Robotics and AI, 8:652417,

Herausgeber:

Frontiers

Seiten:

Open Access:

Peer reviewed:

Ja

Zitierung:

Strutz, Tilo (2021): Traveling Santa Problem: Optimization of a Million-Households Tour Within One Hour. Frontiers in Robotics and AI, 8:652417, 8. DOI: 10.3389/frobt.2021.652417

Autoren:

Tilo Strutz