Exact and Evolutionary Algorithms for Synchronization of Public Transportation Timetables Considering Extended Transfer Zones

Sergio Nesmachnow · Claudio Risso

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Transportation Planning and Optimization Vehicle Routing Optimization Methods Railway Systems and Energy Efficiency

Abstract

This article addresses timetable synchronization in public transportation, an important problem in modern smart cities, in order to guarantee a proper quality of service to citizens. Two variants of the bus timetabling synchronization problem considering extended transfer zones are studied: optimizing offsets and optimizing offsets and headways for each line. An exact mixed integer programming and an evolutionary algorithm are developed to solve both problem variants. The algorithms are evaluated on 45 instances of a real case study, the intelligent transportation system of Montevideo, Uruguay. Experimental results reported significant improvements over the current timetable implemented by the city administration. The number of successful synchronizations improved up to 66.6% and 179.9% for the first and second problem variant, respectively. The average waiting times for transfers improved, especially in tight problem instances (up to 57.8% and 158.3% for the first and second problem variant, respectively). The proposed planning methods are useful to help decision makers to configure public transportation systems.

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References

1986Bus network design 2001Creating bus timetables with maximal synchronization 2012Synchronization of bus timetabling 2010A practical model for transfer optimization in a transit network: Model formulations and solutions 1995Practical Experiences in Schedule Synchronization 2015Multiperiod Bus Timetabling 2004A Model to Create Bus Timetables to Attain Maximum Synchronization Considering Waiting Times at Transfer Stops 2019Transit timetable synchronization for transfer time minimization

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2023Smart Public Transport: A Bi-Objective Model for Maximizing Synchronizations and Minimizing Costs in Bus Timetables 2022Travel Time Estimation in Public Transportation Using Bus Location Data 2023Big Data Analysis for Travel Time Characterization in Public Transportation Systems 2022Integrated Framework for Bus Timetabling and Scheduling in Multi-Line Operation Mode

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