Genetic algorithm based EV scheduling for on-demand public transit system
The popularity of real-time on-demand transit as a fast evolving mobility service has paved the way to explore novel solutions for point-to-point transit requests. In addition, strict government regulations on greenhouse gas emission calls for energy efficient transit solutions. To this end, we prop...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2021
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/147722 |
| _version_ | 1826116398927052800 |
|---|---|
| author | Perera, Thilina Prakash, Alok Srikanthan, Thambipillai |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Perera, Thilina Prakash, Alok Srikanthan, Thambipillai |
| author_sort | Perera, Thilina |
| collection | NTU |
| description | The popularity of real-time on-demand transit as a fast evolving mobility service has paved the way to explore novel solutions for point-to-point transit requests. In addition, strict government regulations on greenhouse gas emission calls for energy efficient transit solutions. To this end, we propose an on-demand public transit system using a fleet of heterogeneous electric vehicles, which provides real-time service to passengers by linking a zone to a predetermined rapid transit node. Subsequently, we model the problem using a Genetic Algorithm, which generates routes and schedules in real-time while minimizing passenger travel time. Experiments performed using a real map show that the proposed algorithm not only generates near-optimal results but also advances the state-of-the-art at a marginal cost of computation time. |
| first_indexed | 2024-10-01T04:11:04Z |
| format | Conference Paper |
| id | ntu-10356/147722 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:11:04Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1477222021-04-21T05:28:08Z Genetic algorithm based EV scheduling for on-demand public transit system Perera, Thilina Prakash, Alok Srikanthan, Thambipillai School of Computer Science and Engineering International Conference on Computational Science 2019 (ICCS) Engineering::Computer science and engineering Intelligent Transport Systems Evolutionary Computation The popularity of real-time on-demand transit as a fast evolving mobility service has paved the way to explore novel solutions for point-to-point transit requests. In addition, strict government regulations on greenhouse gas emission calls for energy efficient transit solutions. To this end, we propose an on-demand public transit system using a fleet of heterogeneous electric vehicles, which provides real-time service to passengers by linking a zone to a predetermined rapid transit node. Subsequently, we model the problem using a Genetic Algorithm, which generates routes and schedules in real-time while minimizing passenger travel time. Experiments performed using a real map show that the proposed algorithm not only generates near-optimal results but also advances the state-of-the-art at a marginal cost of computation time. National Research Foundation (NRF) This research project is partially funded by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme with the Technical University of Munich at TUMCREATE. 2021-04-21T05:28:08Z 2021-04-21T05:28:08Z 2019 Conference Paper Perera, T., Prakash, A. & Srikanthan, T. (2019). Genetic algorithm based EV scheduling for on-demand public transit system. International Conference on Computational Science 2019 (ICCS), 11540 LNCS, 595-603. https://dx.doi.org/10.1007/978-3-030-22750-0_56 9783030227494 https://hdl.handle.net/10356/147722 10.1007/978-3-030-22750-0_56 2-s2.0-85068475010 11540 LNCS 595 603 en NRF TUMCREATE © 2019 Institute of Electrical and Electronics Engineers (IEEE). All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Intelligent Transport Systems Evolutionary Computation Perera, Thilina Prakash, Alok Srikanthan, Thambipillai Genetic algorithm based EV scheduling for on-demand public transit system |
| title | Genetic algorithm based EV scheduling for on-demand public transit system |
| title_full | Genetic algorithm based EV scheduling for on-demand public transit system |
| title_fullStr | Genetic algorithm based EV scheduling for on-demand public transit system |
| title_full_unstemmed | Genetic algorithm based EV scheduling for on-demand public transit system |
| title_short | Genetic algorithm based EV scheduling for on-demand public transit system |
| title_sort | genetic algorithm based ev scheduling for on demand public transit system |
| topic | Engineering::Computer science and engineering Intelligent Transport Systems Evolutionary Computation |
| url | https://hdl.handle.net/10356/147722 |
| work_keys_str_mv | AT pererathilina geneticalgorithmbasedevschedulingforondemandpublictransitsystem AT prakashalok geneticalgorithmbasedevschedulingforondemandpublictransitsystem AT srikanthanthambipillai geneticalgorithmbasedevschedulingforondemandpublictransitsystem |