#6429. Robust transit line planning based on demand estimates obtained from mobile phones

November 2026publication date
Proposal available till 08-06-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Modeling and Simulation;
Management Science and Operations Research;
Transportation;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
The line-planning problem seeks to determine the set of fixed routes (or lines) a transit operator should run, along with associated operation frequencies. We propose an optimization algorithm for the transit-line-planning problem based on bi-level programming that exploits the problems structure in conjunction with the range estimation of demands. The issue of conservativeness due to the range estimation is mitigated by adopting the robust optimization approach. The model was inspired by a real-world application that leverages big data available from telecommunications operators to estimate city-wide mobility patterns. Demand estimates from such sources are based on large sample sizes (often orders of magnitude larger than those used in survey-based approaches), and capture day-to-day variability in travel demand as ranges. The validity of the proposed algorithm is demonstrated by using real-world data derived from 2.5 billion call data records from Abidjan, C?te dIvoire.
Keywords:
Column generation; Mobile phone data; Robust network design; Transit line planning

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