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Planning and Optimizing Transit Lines

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arxiv 2405.10074 v1 pith:M2L2LBQK submitted 2024-05-16 math.OC

classification math.OC
keywords lineplanningtransitdifferentmodelsfrequencylinesperformance
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For all line-based transit systems like bus, metro and tram, the routes of the lines and the frequencies at which they are operated are determining for the operational performance of the system. However, as transit line planning happens early in the planning process, it is not straightforward to predict the effects of line planning decisions on relevant performance indicators. This challenge has in more than 40 years of research on transit line planning let to many different models. In this chapter, we concentrate on models for transit line planning including transit line planning under uncertainty. We pay particular attention to the interplay of passenger routes, frequency and capacity, and specify three different levels of aggregation at which these can be modeled. Transit line planning has been studied in different communities under different names.The problem can be decomposed into the components line generation, line selection, and frequency setting. We include publications that regard one of these individual steps as well as publications that combine two or all of them. We do not restrict to models build with a certain solution approach in mind, but do have a focus on models expressed in the language of mathematical programming.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Line planning under crowding: A cut-and-column generation approach

    math.OC 2025-01 conditional novelty 6.0 of 10

    A mixed-integer second-order cone reformulation with cut-and-column generation produces crowding-aware line plans for the full Beijing metro, cutting crowding at modest travel-time cost.

  2. An ALNS Heuristic for Large-Scale Line Planning with Mode Choice and Line Generation

    math.OC 2026-07 conditional novelty 5.0 of 10

    An ALNS heuristic with dynamic line generation and logit-based endogenous demand produces higher-frequency, higher-ridership bus networks for Odense, but the results depend on hand-set demand-sensitivity parameters.

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