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Evolutionary Approach for the Multi-objective Bike Routing Problem

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Computational Logistics (ICCL 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12433))

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Abstract

In this paper, a multi-objective approach for the bike routing problem is presented. Bike routing represents specific challenges, since cyclists have different experiences, concerns, and route preferences. Our approach considers two criteria: the total traveled distance and the cyclists safety. Finding the optimal Pareto set is computationally unfeasible for these problems, therefore, the goal of this work is to create a non-exact method capable of producing a set of quality solutions in a timely manner. A heuristic that modifies the multi-label setting algorithm is used to create an initial population and a genetic elitist algorithm is used to find an approximated Pareto set of optimal routes. The proposed methodology is applied on a practical case study, in which real data from OpenStreetMaps (OSM) and Shuttle Radar Topography Mission (SRTM) was used to model the graph for the road network of the city of Aveiro, with 9506 nodes and 21208 edges. The results show that the approach is fast enough for interactive use in a planning tool and produces a set of quality solutions, regarding two criteria, the traveled distance and the safety of the path.

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Acknowledgments

The authors acknowledge the financial Support through project POCI-01-0247-FEDER-033769 - “Ghisallo - Investigação e Desenvolvimento de uma nova solução de comutação urbana, assente num novo conceito de veículo elétrico de próxima geração” which was funded by the Operational Program for Competiveness and Internationalization (COMPETE 2020) in its component FEDER and UID/EMS/00481 /2013-FCT CENTRO-01-0145 FEDER-022083 POCI-01-0247-FEDER-033769.

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Authors and Affiliations

  1. University of Aveiro, Aveiro, Portugal

    Pedro Nunes, Ana Moura & José Santos

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  1. Pedro Nunes
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  2. Ana Moura
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  3. José Santos
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Correspondence to Pedro Nunes .

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Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Eduardo Lalla-Ruiz

  2. University of Twente, Enschede, The Netherlands

    Martijn Mes

  3. University of Hamburg, Hamburg, Germany

    Stefan Voß

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Nunes, P., Moura, A., Santos, J. (2020). Evolutionary Approach for the Multi-objective Bike Routing Problem. In: Lalla-Ruiz, E., Mes, M., Voß, S. (eds) Computational Logistics. ICCL 2020. Lecture Notes in Computer Science(), vol 12433. Springer, Cham. https://doi.org/10.1007/978-3-030-59747-4_20

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  • DOI: https://doi.org/10.1007/978-3-030-59747-4_20

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-59747-4

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