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Sustainability-Oriented Route Generation for Ridesharing Services

Mengya Liu¹, Vahid Yazdanpanah², Sebastian Stein² and Enrico Gerding²

1. Smart Data Group, AI Lab, Lenovo Research at Lenovo
   No 10 Courtyard, Xibeiwang, East Road, Haidian District, Beijing, China, 100094
   myliu26@lenovo.com
2. Agents, Interaction and Complexity Research Group, University of Southampton
   SO17 1BJ, Southampton, UK
   v.yazdanpanah@soton.ac.uk, ss2@ecs.soton.ac.uk, eg@ecs.soton.ac.uk

Abstract

Sustainability is the ability to maintain and preserve natural and manmade systems for the benefit of current and future generations. The three pillars of sustainability are social, economic, and environmental. These pillars are interdependent and interconnected, meaning that progress in one area can have positive or negative impacts on the others. This calls for smart methods to balance such benefits and find solutions that are optimal with respect to all the three pillars of sustainability. By using AI methods, in particular, genetic algorithms for multiobjective optimisation, we can better understand and manage complex systems in order to achieve sustainability. In the context of sustainability-oriented ridesharing, genetic algorithms can be used to optimise route finding in order to lower the cost of transportation and reduce emissions. This work contributes to this domain by using AI, specifically genetic algorithms for multiobjective optimisation, to improve the efficiency and sustainability of transportation systems. By using this approach, we can make progress towards achieving the goals of the three pillars of sustainability.

Key words

Ridesharing, Multiobjective Algorithm, Mobility-on-demand, Sustainable Transportation, Evolutionary Computation

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS221209053L

Publication information

Volume 21, Issue 1 (January 2024)
Year of Publication: 2024
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Liu, M., Yazdanpanah, V., Stein, S., Gerding, E.: Sustainability-Oriented Route Generation for Ridesharing Services. Computer Science and Information Systems, Vol. 21, No. 1, 309–333. (2024), https://doi.org/10.2298/CSIS221209053L