poster

Public transport timetable and charge optimization using multiple electric buses types

Authors:

Bernabé Dorronsoro,

Andrei Tchernykh,

Patricia RuizAuthors Info & Claims

GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 751 - 754

https://doi.org/10.1145/3520304.3528959

Published: 19 July 2022 Publication History

Abstract

Electrification of transportation brings novel opportunities and challenges in designing new sustainable public transport systems. The adoption of electric buses implies the need for new models that consider the autonomy of batteries, charging opportunities, users' demand, and the capacity of vehicles, among others. We model the problem of a bus lane in Los Angeles as a combinatorial optimization problem and use the available information to obtain the optimal timetable and fleet of buses. For that, an accurate mathematical model to calculate the consumption of each type of bus is defined, and the problem is solved with a genetic algorithm. Thanks to the strategic schedules found by the proposed approach, the buses culminate the day with 26.5% of energy on average. Just 6.5% over the minimum safety threshold required to preserve the battery state of health (20%). Our approach optimizes the number of buses needed and their battery utilization based on the energy consumption per trip, the regenerative braking, and overnight recharging.

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Cited By

Peña DMassobrio RDorronsoro BNesmachnow SRuiz P(2024)Designing a Sustainable Bus Transport System with High QoS Using Computational IntelligenceEncyclopedia of Sustainable Technologies10.1016/B978-0-323-90386-8.00043-7(697-710)Online publication date: 2024
https://doi.org/10.1016/B978-0-323-90386-8.00043-7
Diaz EMuñoz-Añasco MSalvador AGarcía E(2023)Simulation model for the study of maintenance actions in a homogeneous multi-unit system of interchangeable components, with cannibalizationReliability Engineering & System Safety10.1016/j.ress.2023.109532240(109532)Online publication date: Dec-2023
https://doi.org/10.1016/j.ress.2023.109532

Index Terms

Public transport timetable and charge optimization using multiple electric buses types
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Bio-inspired approaches
        Genetic algorithms
2. Mathematics of computing
  1. Discrete mathematics
    1. Combinatorics
      1. Combinatorial optimization

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Information

Published In

cover image ACM Conferences

GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2022

2395 pages

ISBN:9781450392686

DOI:10.1145/3520304

Editor:
Jonathan E. Fieldsend
University of Exeter
,
General Chair:
Markus Wagner
The University of Adelaide

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2022

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Poster

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Russian Foundation for Basic Research
European Regional Development Fund
Junio de Andalucia
Spanish Ministerio de Ciencia, Innovación y Universidades

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GECCO '22

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SIGEVO

GECCO '22: Genetic and Evolutionary Computation Conference

July 9 - 13, 2022

Massachusetts, Boston

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Peña DMassobrio RDorronsoro BNesmachnow SRuiz P(2024)Designing a Sustainable Bus Transport System with High QoS Using Computational IntelligenceEncyclopedia of Sustainable Technologies10.1016/B978-0-323-90386-8.00043-7(697-710)Online publication date: 2024
https://doi.org/10.1016/B978-0-323-90386-8.00043-7
Diaz EMuñoz-Añasco MSalvador AGarcía E(2023)Simulation model for the study of maintenance actions in a homogeneous multi-unit system of interchangeable components, with cannibalizationReliability Engineering & System Safety10.1016/j.ress.2023.109532240(109532)Online publication date: Dec-2023
https://doi.org/10.1016/j.ress.2023.109532

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