Robust timetable optimization for bus lines subject to resource and regulatory constraints

K. Gkiotsalitis, F. Alesiani

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Timetables are typically generated based on passenger demand and travel time expectations. This work incorporates the travel time and passenger demand uncertainty to generate robust timetables that minimize the possible loss at worst-case scenarios. We solve the resulting minimax problem with a genetic algorithm that uses sequential quadratic programming to evaluate the worst-case performance of each population member. Our approach is tested on a bus line in Singapore demonstrating an improvement potential of on service regularity and excessive trip travel times.
Original languageEnglish
Pages (from-to)30-51
JournalTransportation research. Part E: Logistics and transportation review
Volume128
DOIs
Publication statusPublished - 1 Aug 2019

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Travel time
travel
resources
demand
Quadratic programming
regularity
Singapore
programming
Genetic algorithms
uncertainty
scenario
performance
time
Robust optimization
Bus
Resources

Cite this

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Robust timetable optimization for bus lines subject to resource and regulatory constraints. / Gkiotsalitis, K.; Alesiani, F.

In: Transportation research. Part E: Logistics and transportation review, Vol. 128, 01.08.2019, p. 30-51.

Research output: Contribution to journalArticleAcademicpeer-review

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