A Neural-Evolutionary Algorithm for Autonomous Transit Network Design
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916424957558784 |
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| author | Holliday, Andrew Dudek, Gregory |
| author_facet | Holliday, Andrew Dudek, Gregory |
| contents | Planning a public transit network is a challenging optimization problem, but essential in order to realize the benefits of autonomous buses. We propose a novel algorithm for planning networks of routes for autonomous buses. We first train a graph neural net model as a policy for constructing route networks, and then use the policy as one of several mutation operators in a evolutionary algorithm. We evaluate this algorithm on a standard set of benchmarks for transit network design, and find that it outperforms the learned policy alone by up to 20% and a plain evolutionary algorithm approach by up to 53% on realistic benchmark instances. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2403_07917 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Neural-Evolutionary Algorithm for Autonomous Transit Network Design Holliday, Andrew Dudek, Gregory Neural and Evolutionary Computing Machine Learning Planning a public transit network is a challenging optimization problem, but essential in order to realize the benefits of autonomous buses. We propose a novel algorithm for planning networks of routes for autonomous buses. We first train a graph neural net model as a policy for constructing route networks, and then use the policy as one of several mutation operators in a evolutionary algorithm. We evaluate this algorithm on a standard set of benchmarks for transit network design, and find that it outperforms the learned policy alone by up to 20% and a plain evolutionary algorithm approach by up to 53% on realistic benchmark instances. |
| title | A Neural-Evolutionary Algorithm for Autonomous Transit Network Design |
| topic | Neural and Evolutionary Computing Machine Learning |
| url | https://arxiv.org/abs/2403.07917 |