A4 Article in conference proceedings
Time-Dependent Multiple Depot Vehicle Routing Problem on Megapolis Network under Wardrop's Traffic Flow Assignment (2018)

Mugayskikh, A. V., Zakharov, V. V., & Tuovinen, T. (2018). Time-Dependent Multiple Depot Vehicle Routing Problem on Megapolis Network under Wardrop's Traffic Flow Assignment. In S. Baladin, T. Hämäläinen, & T. Tyutina (Eds.), FRUCT : Proceedings of the 22nd Conference of Open Innovations Association (pp. 173-178). IEEE. Proceedings of Conference of Open Innovations Association FRUCT. https://doi.org/10.23919/FRUCT.2018.8468273

JYU authors or editors

Publication details

All authors or editors: Mugayskikh, Alexander V.; Zakharov, Victor V.; Tuovinen, Tero

Parent publication: FRUCT : Proceedings of the 22nd Conference of Open Innovations Association

Parent publication editors: Baladin, Sergey; Hämäläinen, Timo; Tyutina, Tatiana

ISBN: 978-952-68653-4-8

Journal or series: Proceedings of Conference of Open Innovations Association FRUCT

ISSN: 2305-7254

eISSN: 2343-0737

Publication year: 2018

Pages range: 173-178

Number of pages in the book: 426

Publisher: IEEE

Publication country: United States

Publication language: English

DOI: https://doi.org/10.23919/FRUCT.2018.8468273

Persistent website address: https://fruct.org/publications/fruct22/files/Mug.pdf

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/60880

Additional information: Proceedings of the 22nd Conference of Open Innovations Association FRUCT. Jyväskylä, Finland, 15-18 May 2018.

Abstract

In this work multiple depot vehicle routing problem is considered in case of variable travel times between nodes on a metropolis network. This variant of the classic multiple depot vehicle routing problem is motivated by the fact that in urban contexts variable traffic conditions play an essential role and can not be ignored in order to perform a realistic optimization. Time-travel matrices corresponding to each period of planning horizon were formed by solving the traffic assignment problem in conjunction with shortest path problem. Routing problem instances include from 20 to 100 customers randomly chosen from a road network of Saint-Petersburg. The results demonstrate that taking into account traffic flow information can reduce route time by 8-37% depending on number of customers in the problem instance.

Keywords: routing; roads; optimisation; planning and design

Free keywords: vehicle routing; biological system modeling; optimization; planning

Contributing organizations

Related projects

Ministry reporting: Yes

Reporting Year: 2018

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