research-article

Multi-objective optimization of level of service in urban transportation

Authors:

Hernan Aguirre,

Kiyoshi TanakaAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference

Pages 1057 - 1064

https://doi.org/10.1145/3071178.3071262

Published: 01 July 2017 Publication History

Abstract

This work investigates levels of service in urban transportation coupling a multi-objective evolutionary algorithm with the multi-agent traffic simulator MATSim. The evolutionary algorithm searches combinations of number of private/public transportation users, capacity of buses, and time interval between bus departures minimizing traffic density, travel time and fuel consumption simultaneously. MATSim simulates the movement of 27.000 agents according to the solutions of the evolutionary algorithm on a model of the traffic network of Quito city. We study the trade-off in objectives and analyze the solutions produced to gain knowledge about the conditions to achieve different levels of service. Also, we analyze particulate matter emissions for the trade-off solutions. This work is useful for decision makers to suggest policies that can improve mobility combining private and public transportation.

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Cited By

Vendi VFonlupt CVerel S(2024)Benchmark Mobility Problems Using Real-World Data: The Example of Bus Stops Spacing Problem for the City of CalaisProceeding of the 7th International Conference on Logistics Operations Management, GOL'2410.1007/978-3-031-68634-4_10(105-113)Online publication date: 21-Sep-2024
https://doi.org/10.1007/978-3-031-68634-4_10
Vendi VVerel SFonlupt C(2024)Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing ProblemEvolutionary Computation in Combinatorial Optimization10.1007/978-3-031-57712-3_2(16-32)Online publication date: 2024
https://doi.org/10.1007/978-3-031-57712-3_2
Del Ser JOsaba ESanchez-Medina JFister IFister I(2020)Bioinspired Computational Intelligence and Transportation Systems: A Long Road AheadIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2019.289737721:2(466-495)Online publication date: Feb-2020
https://doi.org/10.1109/TITS.2019.2897377

Index Terms

Multi-objective optimization of level of service in urban transportation
1. Applied computing
  1. Operations research
    1. Transportation
2. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
      1. Discrete optimization
        Optimization with randomized search heuristics
        Evolutionary algorithms

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cover image ACM Conferences

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference

July 2017

1427 pages

ISBN:9781450349208

DOI:10.1145/3071178

General Chair:
Peter A. N. Bosman
Centrum Wiskunde & Informatica (CWI)

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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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

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Published: 01 July 2017

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GECCO '17

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SIGEVO

GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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GECCO '17 Paper Acceptance Rate 178 of 462 submissions, 39%;

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

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Cited By

Vendi VFonlupt CVerel S(2024)Benchmark Mobility Problems Using Real-World Data: The Example of Bus Stops Spacing Problem for the City of CalaisProceeding of the 7th International Conference on Logistics Operations Management, GOL'2410.1007/978-3-031-68634-4_10(105-113)Online publication date: 21-Sep-2024
https://doi.org/10.1007/978-3-031-68634-4_10
Vendi VVerel SFonlupt C(2024)Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing ProblemEvolutionary Computation in Combinatorial Optimization10.1007/978-3-031-57712-3_2(16-32)Online publication date: 2024
https://doi.org/10.1007/978-3-031-57712-3_2
Del Ser JOsaba ESanchez-Medina JFister IFister I(2020)Bioinspired Computational Intelligence and Transportation Systems: A Long Road AheadIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2019.289737721:2(466-495)Online publication date: Feb-2020
https://doi.org/10.1109/TITS.2019.2897377

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