Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm

Stefan Vonolfen; Michael Affenzeller; Andreas Beham; Stefan Wagner

doi:10.1109/LINDI.2011.6031155

Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm

Stefan Vonolfen, Michael Affenzeller, Andreas Beham, Stefan Wagner

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag

9 Zitate (Scopus)

Abstract

The vehicle routing problem is a class of problems that frequently occurs in the field of transportation logistics. In this work, we tackle very-large scale problem instances with time windows. Among other techniques, metaheuristics are frequently used to solve large-scale instances close to optimality. We present an island-model genetic algorithm variant and apply several techniques such as offspring selection and adaptive constraint relaxation. To validate our approach, we perform test runs on benchmark instances with 1000 customers and compare the results to the currently best-known solutions.

Originalsprache	Englisch
Titel	LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings
Seiten	27-31
Seitenumfang	5
DOIs	https://doi.org/10.1109/LINDI.2011.6031155
Publikationsstatus	Veröffentlicht - 2011
Veranstaltung	3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI 2011) - Budapest, Ungarn Dauer: 25 Aug. 2011 → 27 Aug. 2011 http://conf.uni-obuda.hu/lindi2011/

Publikationsreihe

Name	LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings

Konferenz

Konferenz	3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI 2011)
Land/Gebiet	Ungarn
Ort	Budapest
Zeitraum	25.08.2011 → 27.08.2011
Internetadresse	http://conf.uni-obuda.hu/lindi2011/

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10.1109/LINDI.2011.6031155

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Vonolfen, S., Affenzeller, M., Beham, A., & Wagner, S. (2011). Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm. in LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings (S. 27-31). Artikel 6031155 (LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings). https://doi.org/10.1109/LINDI.2011.6031155

Vonolfen, Stefan ; Affenzeller, Michael ; Beham, Andreas et al. / Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm. LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings. 2011. S. 27-31 (LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings).

@inproceedings{b3182bf6fadc4e7491747fd8329f94b8,

title = "Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm",

abstract = "The vehicle routing problem is a class of problems that frequently occurs in the field of transportation logistics. In this work, we tackle very-large scale problem instances with time windows. Among other techniques, metaheuristics are frequently used to solve large-scale instances close to optimality. We present an island-model genetic algorithm variant and apply several techniques such as offspring selection and adaptive constraint relaxation. To validate our approach, we perform test runs on benchmark instances with 1000 customers and compare the results to the currently best-known solutions.",

keywords = "island-model genetic algorithm, offspring selection, Vehicle routing problem",

author = "Stefan Vonolfen and Michael Affenzeller and Andreas Beham and Stefan Wagner",

year = "2011",

doi = "10.1109/LINDI.2011.6031155",

language = "English",

isbn = "9781457718410",

series = "LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings",

pages = "27--31",

booktitle = "LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings",

note = "3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI 2011) ; Conference date: 25-08-2011 Through 27-08-2011",

url = "http://conf.uni-obuda.hu/lindi2011/",

}

Vonolfen, S, Affenzeller, M, Beham, A & Wagner, S 2011, Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm. in LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings., 6031155, LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings, S. 27-31, 3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI 2011), Budapest, Ungarn, 25.08.2011. https://doi.org/10.1109/LINDI.2011.6031155

Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm. / Vonolfen, Stefan; Affenzeller, Michael; Beham, Andreas et al.
LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings. 2011. S. 27-31 6031155 (LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag

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T1 - Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm

AU - Vonolfen, Stefan

AU - Affenzeller, Michael

AU - Beham, Andreas

AU - Wagner, Stefan

PY - 2011

Y1 - 2011

N2 - The vehicle routing problem is a class of problems that frequently occurs in the field of transportation logistics. In this work, we tackle very-large scale problem instances with time windows. Among other techniques, metaheuristics are frequently used to solve large-scale instances close to optimality. We present an island-model genetic algorithm variant and apply several techniques such as offspring selection and adaptive constraint relaxation. To validate our approach, we perform test runs on benchmark instances with 1000 customers and compare the results to the currently best-known solutions.

AB - The vehicle routing problem is a class of problems that frequently occurs in the field of transportation logistics. In this work, we tackle very-large scale problem instances with time windows. Among other techniques, metaheuristics are frequently used to solve large-scale instances close to optimality. We present an island-model genetic algorithm variant and apply several techniques such as offspring selection and adaptive constraint relaxation. To validate our approach, we perform test runs on benchmark instances with 1000 customers and compare the results to the currently best-known solutions.

KW - island-model genetic algorithm

KW - offspring selection

KW - Vehicle routing problem

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U2 - 10.1109/LINDI.2011.6031155

DO - 10.1109/LINDI.2011.6031155

M3 - Conference contribution

SN - 9781457718410

T3 - LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings

SP - 27

EP - 31

BT - LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings

T2 - 3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI 2011)

Y2 - 25 August 2011 through 27 August 2011

ER -

Vonolfen S, Affenzeller M, Beham A, Wagner S. Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm. in LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings. 2011. S. 27-31. 6031155. (LINDI 2011 - 3rd IEEE International Symposium on Logistics and Industrial Informatics, Proceedings). doi: 10.1109/LINDI.2011.6031155

Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm

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