Optimize Hybrid Genetic Search for Vehicle Routing
3 weken geleden
Job Opportunity
At ORTEC, we are seeking a talented master student to contribute to the development of our hybrid genetic search algorithm for the Vehicle Routing Problem with Time Windows (VRPTW). This algorithm has already demonstrated exceptional performance in the DIMACS 2022 challenge, and we aim to further enhance its capabilities.
Your Challenge
You will work on PyVRP, an open-source implementation of the hybrid genetic search algorithm, to evaluate its performance on large real-world problem instances and push its limits to maximize efficiency. You will have the freedom to explore various optimization strategies, including parameter tuning, initialization techniques, and genetic algorithm concepts, as well as leveraging machine learning to guide internal decisions.
Requirements
- You are a master student in computer science, operations research, or artificial intelligence.
- You are proficient in Python and have experience with optimization algorithms.
- Experience with compiled languages like C++ and/or running computational jobs on cloud infrastructure is a plus.
- You are currently living in the Netherlands and studying at a Dutch University.
- You communicate fluently in English, both verbally and in writing.
- You are available for 6 months, working 32-40 hours per week.
What We Offer
- A dynamic and passionate work environment at ORTEC, where you will be part of a team that shares a drive to use problem-solving skills to improve our planet.
- Excellent supervision during your graduation project, as well as a good internship allowance, laptop, and other office facilities.
- An open, kind, and fun culture, with opportunities to attend courses and seminars, and work abroad.
Next Steps
Please upload your CV, motivation letter, and grade lists (BSc and MSc in one PDF if applicable). The recruitment process will consist of two online assessments, a first interview, and a second interview with a case.
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