Abstract
Addressing school bus routing problem is important to ensure a safe and cost effective solution for students, parents and stakeholders. However, challenges in terms of multiple constraints and objectives are present. In this paper, school bus routing problem is formulated as contained multi-objective optimization problem. Cluster-first route-second scheme, genetic algorithm and adaptive genetic algorithm are applied to solve this problem. The performance of these algorithms are evaluated using real data of public schools in the City of Winchester, Virginia, USA. The conducted experiments showed that Cluster-first route-second yields the optimal solution.
| Original language | English |
|---|---|
| Title of host publication | 2023 IEEE International Conference on Smart Mobility, SM 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 33-38 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798350312751 |
| DOIs | |
| State | Published - 2023 |
| Externally published | Yes |
| Event | 2023 IEEE International Conference on Smart Mobility, SM 2023 - Thuwal, Saudi Arabia Duration: 19 Mar 2023 → 21 Mar 2023 |
Publication series
| Name | 2023 IEEE International Conference on Smart Mobility, SM 2023 |
|---|
Conference
| Conference | 2023 IEEE International Conference on Smart Mobility, SM 2023 |
|---|---|
| Country/Territory | Saudi Arabia |
| City | Thuwal |
| Period | 19/03/23 → 21/03/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Ant Colony System
- Cluster-first route-second
- Genetic Algorithm
- Metaheuristics
- school Bus Routing
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Control and Optimization
- Transportation