An ALNS algorithm for the static dial-a-ride problem with ride and waiting time minimization

Christian Pfeiffer () and Arne Schulz ()
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Christian Pfeiffer: University of Hamburg
Arne Schulz: University of Hamburg

OR Spectrum: Quantitative Approaches in Management, 2022, vol. 44, issue 1, No 4, 87-119

Abstract: Abstract The paper investigates the static dial-a-ride problem with ride and waiting time minimization. This is a new problem setting of significant practical relevance because several ride-sharing providers launched in recent years in large European cities. In contrast to the standard dial-a-ride problem, these providers focus on the general public. Therefore, they are amongst others in competition with taxis and private cars, which makes a more customer-oriented objective necessary. We present an adaptive large neighbourhood search (ALNS) as well as a dynamic programming algorithm (DP), which are tested in comprehensive computational studies. Although the DP can only be used for a single tour and, due to the computational effort, as a restricted version or for small instances, the ALNS also works efficiently for larger instances. The results indicate that ride-sharing proposals may help to solve the trade-off between individual transport, profitability of the provider, and reduction of traffic and pollution.

Keywords: Demand responsive transport; Dial-a-ride; Adaptive large neighbourhood search; Dynamic programming (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s00291-021-00656-7

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