A1 Journal article (refereed)
On automatic algorithm configuration of vehicle routing problem solvers (2019)

Rasku, J., Musliu, N., & Kärkkäinen, T. (2019). On automatic algorithm configuration of vehicle routing problem solvers. In J. Rasku (Ed.), Toward automatic customization of vehicle routing systems (2, pp. 1-22). Springer. Journal on Vehicle Routing Algorithms. https://doi.org/10.1007/s41604-019-00010-9

JYU authors or editors

Publication details

All authors or editors: Rasku, Jussi; Musliu, Nysret; Kärkkäinen, Tommi

Parent publication: Toward automatic customization of vehicle routing systems

Parent publication editors: Rasku, Jussi

eISBN: 978-951-39-7826-6

Journal or series: Journal on Vehicle Routing Algorithms

ISSN: 2367-3591

eISSN: 2489-9003

Publication year: 2019

Volume: 2

Issue number: 1-4

Pages range: 1-22

Number of pages in the book: 1 verkkoaineisto (97 sivua, 173 sivua useina numerointijaksoina, 28 numeroimatonta sivua) :

Publisher: Springer

Place of Publication: Jyväskylä

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1007/s41604-019-00010-9

Persistent website address: http://urn.fi/URN:ISBN:978-951-39-7826-6

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/66462


Many of the algorithms for solving vehicle routing problems expose parameters that strongly influence the quality of obtained solutions and the performance of the algorithm. Finding good values for these parameters is a tedious task that requires experimentation and experience. Therefore, methods that automate the process of algorithm configuration have received growing attention. In this paper, we present a comprehensive study to critically evaluate and compare the capabilities and suitability of seven state-of-the-art methods in configuring vehicle routing metaheuristics. The configuration target is the solution quality of eight metaheuristics solving two vehicle routing problem variants. We show that the automatic algorithm configuration methods find good parameters for the vehicle route optimization metaheuristics and clearly improve the solutions obtained over default parameters. Our comparison shows that despite some observable differences in configured performance there is no single configuration method that always outperforms the others. However, largest gains in performance can be made by carefully selecting the right configurator. The findings of this paper may give insights on how to effectively choose and extend automatic parameter configuration methods and how to use them to improve vehicle routing solver performance.

Keywords: vehicles; routing; automatic control; automation systems; algorithms; optimisation

Free keywords: vehicle routing problem; automatic algorithm configuration; metaheuristics; meta-optimization

Contributing organizations

Other organizations:

Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1

Last updated on 2023-27-02 at 10:44