Learning to optimize timetables for efficient transfers in public transportation systems-Reference-Cited by-同舟云学术

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Learning to optimize timetables for efficient transfers in public transportation systems

Published:2022-04 Issue: Volume:119 Page:108616
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Massobrio Renzo^ORCID,Nesmachnow Sergio^ORCID,Muraña Jonathan^ORCID,Dorronsoro Bernabé^ORCID

Publisher

Elsevier BV

Subject

Software

Reference42 articles.

1. Urban Transportation Systems;Grava,2002

2. A distributed platform for big data analysis in smart cities: combining intelligent transportation systems and socioeconomic data for Montevideo, Uruguay;Nesmachnow;EAI Endorsed Trans. Smart Cities,2017

3. Bus network design;Ceder;Transp. Res. B,1986

4. Timetable synchronization for buses;Ceder,1999

5. Complexity and Approximation: Combinatorial Optimization Problems and their Approximability Properties;Ausiello,2012

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1. Machine Learning for public transportation demand prediction: A Systematic Literature Review;Engineering Applications of Artificial Intelligence;2024-11

2. Smart City Public Transportation Route Planning Based on Multi-objective Optimization: A Review;Archives of Computational Methods in Engineering;2024-03-08

3. Smart Public Transport: A Bi-Objective Model for Maximizing Synchronizations and Minimizing Costs in Bus Timetables;Applied Sciences;2023-12-06

4. Evaluation of Stated Preference Surveys with Statistical Methods;Promet - Traffic&Transportation;2023-10-30

5. Analyzing the Influencing Factors on Bus-Metro Transfer Ridership Incorporating Spatial Heterogeneity Based on Multi-Source Data;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24

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