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
Abstract
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
Ministry reporting: Yes
VIRTA submission year: 2019
JUFO rating: 1
