Improvements for mlrose Applied to the Traveling Salesperson Problem.

Stefan Wintersteller; Martin Uray; Michael Lehenauer; Stefan Huber

doi:10.1007/978-3-031-25312-6_72

Improvements for mlrose Applied to the Traveling Salesperson Problem.

Stefan Wintersteller, Martin Uray, Michael Lehenauer, Stefan Huber

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper we discuss the application of Artificial Intelligence (AI) to the exemplary industrial use case of the two-dimensional commissioning problem in a high-bay storage, which essentially can be phrased as an instance of Traveling Salesperson Problem (TSP).

We investigate the mlrose library that provides an TSP optimizer based on various heuristic optimization techniques. Our focus is on two methods, namely Genetic Algorithm (GA) and Hill Climbing (HC), which are provided by mlrose. We present improvements for both methods that yield shorter tour lengths, by moderately exploiting the problem structure of TSP. That is, the proposed improvements have a generic character and are not limited to TSP only.

Original language	English
Title of host publication	Computer Aided Systems Theory – EUROCAST 2022
Subtitle of host publication	18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers
Publisher	Springer Nature
Pages	611-618
Number of pages	8
Volume	13789 LNCS
ISBN (Electronic)	978-3-031-25312-6
ISBN (Print)	978-3-031-25311-9
DOIs	https://doi.org/10.1007/978-3-031-25312-6_72
Publication status	Published - 10 Feb 2023
Event	18th International Conference on Computer Aided Systems Theory, EUROCAST 2022 - Las Palmas de Gran Canaria, Spain Duration: 20 Feb 2022 → 25 Feb 2022 https://eurocast2022.fulp.ulpgc.es/

Publication series

Name	Lecture Notes in Computer Science
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Computer Aided Systems Theory, EUROCAST 2022
Abbreviated title	EUROCAST 2022
Country/Territory	Spain
City	Las Palmas de Gran Canaria
Period	20/02/22 → 25/02/22
Internet address	https://eurocast2022.fulp.ulpgc.es/

Classification according to Österreichische Systematik der Wissenschaftszweige (ÖFOS 2012)

102001 Artificial intelligence

Applied Research Level (ARL)

ARL Level 3 - Proof of the functionality of a principle

Research focus/foci

Industrial Informatics

Access to Document

10.1007/978-3-031-25312-6_72

Cite this

Wintersteller, S., Uray, M., Lehenauer, M., & Huber, S. (2023). Improvements for mlrose Applied to the Traveling Salesperson Problem. In Computer Aided Systems Theory – EUROCAST 2022: 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers (Vol. 13789 LNCS, pp. 611-618). (Lecture Notes in Computer Science). Springer Nature. https://doi.org/10.1007/978-3-031-25312-6_72

Wintersteller, Stefan ; Uray, Martin ; Lehenauer, Michael et al. / Improvements for mlrose Applied to the Traveling Salesperson Problem. Computer Aided Systems Theory – EUROCAST 2022: 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers. Vol. 13789 LNCS Springer Nature, 2023. pp. 611-618 (Lecture Notes in Computer Science).

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abstract = "In this paper we discuss the application of Artificial Intelligence (AI) to the exemplary industrial use case of the two-dimensional commissioning problem in a high-bay storage, which essentially can be phrased as an instance of Traveling Salesperson Problem (TSP). We investigate the mlrose library that provides an TSP optimizer based on various heuristic optimization techniques. Our focus is on two methods, namely Genetic Algorithm (GA) and Hill Climbing (HC), which are provided by mlrose. We present improvements for both methods that yield shorter tour lengths, by moderately exploiting the problem structure of TSP. That is, the proposed improvements have a generic character and are not limited to TSP only.",

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Wintersteller, S, Uray, M, Lehenauer, M & Huber, S 2023, Improvements for mlrose Applied to the Traveling Salesperson Problem. in Computer Aided Systems Theory – EUROCAST 2022: 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers. vol. 13789 LNCS, Lecture Notes in Computer Science, Springer Nature, pp. 611-618, 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022, Las Palmas de Gran Canaria, Spain, 20/02/22. https://doi.org/10.1007/978-3-031-25312-6_72

Improvements for mlrose Applied to the Traveling Salesperson Problem. / Wintersteller, Stefan; Uray, Martin; Lehenauer, Michael et al.
Computer Aided Systems Theory – EUROCAST 2022: 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers. Vol. 13789 LNCS Springer Nature, 2023. p. 611-618 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2023/2/10

Y1 - 2023/2/10

N2 - In this paper we discuss the application of Artificial Intelligence (AI) to the exemplary industrial use case of the two-dimensional commissioning problem in a high-bay storage, which essentially can be phrased as an instance of Traveling Salesperson Problem (TSP). We investigate the mlrose library that provides an TSP optimizer based on various heuristic optimization techniques. Our focus is on two methods, namely Genetic Algorithm (GA) and Hill Climbing (HC), which are provided by mlrose. We present improvements for both methods that yield shorter tour lengths, by moderately exploiting the problem structure of TSP. That is, the proposed improvements have a generic character and are not limited to TSP only.

AB - In this paper we discuss the application of Artificial Intelligence (AI) to the exemplary industrial use case of the two-dimensional commissioning problem in a high-bay storage, which essentially can be phrased as an instance of Traveling Salesperson Problem (TSP). We investigate the mlrose library that provides an TSP optimizer based on various heuristic optimization techniques. Our focus is on two methods, namely Genetic Algorithm (GA) and Hill Climbing (HC), which are provided by mlrose. We present improvements for both methods that yield shorter tour lengths, by moderately exploiting the problem structure of TSP. That is, the proposed improvements have a generic character and are not limited to TSP only.

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Wintersteller S, Uray M, Lehenauer M, Huber S. Improvements for mlrose Applied to the Traveling Salesperson Problem. In Computer Aided Systems Theory – EUROCAST 2022: 18th International Conference, Las Palmas de Gran Canaria, Spain, February 20–25, 2022, Revised Selected Papers. Vol. 13789 LNCS. Springer Nature. 2023. p. 611-618. (Lecture Notes in Computer Science). doi: 10.1007/978-3-031-25312-6_72

Improvements for mlrose Applied to the Traveling Salesperson Problem.

Abstract

Publication series

Conference

Classification according to Österreichische Systematik der Wissenschaftszweige (ÖFOS 2012)

Applied Research Level (ARL)

Research focus/foci

Access to Document

Fingerprint

Cite this