Reinforcement learning for vehicle routing
Vehicle routing has been extensively studied in optimization problems. With the advance of AI and big data, this project aims to solve vehicle routing problems (VRP) using reinforcement learning.
M.S. are welcome to register my research credits during the semesters and summer. The student involved in this project will conduct a comprehensive literature review on VRP and develop a RL model. Students with good computer and coding skills are preferred. Skill requirements are:
- Familiar with reinforcement learning models.
- Familiar with Python. Generating figures, graphs, tables, or statistical models to present results with python.
- Creating simulation environment in SUMO (a traffic simulator).
This is an UNPAID research project.
Faculty Advisor
- Professor: Sharon Di
- Center/Lab:
Project Timeline
- Earliest starting date: 9/1/21
- End date: 12/31/21
- Number of hours per week of research expected during Fall 2021: ~20
- Number of hours per week of research expected during Summer 2022: ~30
Candidate requirements
- Skill sets: programming, reinforcement learning modeling, literature review
- Student eligibility:
freshman,sophomore,junior,senior, master’s - International students on F1 or J1 visa: eligible
- Academic Credit Possible: Yes