Stochastic Dynamic Vehicle Routing Problem
| dc.contributor.author | Akhmetbek Y. | |
| dc.date.accessioned | 2025-04-02T05:38:17Z | |
| dc.date.available | 2025-04-02T05:38:17Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The Stochastic Dynamic Vehicle Routing Problem (SDVRP), in which customer demands are dynamic and follow a Poisson distribution, is examined in this study. We provide an SDVRP-specific Reinforcement Learning (RL) algorithm and evaluate it against algorithms for Random Selection, Largest-Demand Selection, and Max-Reachable Selection. We also use a Multi-head Attention architecture into our RL algorithm to better capture complex relationships in the dynamic routing environment. We show, by thorough evaluation, how RL with Multi-head Attention may be used to optimize resource usage and route efficiency, providing useful insights for addressing challenging logistics problems in real-world situations. | |
| dc.identifier.citation | Akhmetbek Y / Stochastic Dynamic Vehicle Routing Problem / 2024 / Computer Science - 7M06102 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1678 | |
| dc.language.iso | en | |
| dc.publisher | Faculty of Engineering and Natural Science | |
| dc.title | Stochastic Dynamic Vehicle Routing Problem | |
| dc.type | Other |