Optimization Expert for Vehicle Routing Challenges
1 week geleden
Job Overview
At ORTEC, we are seeking a highly skilled optimization expert to contribute to our Vehicle Routing Problem with Time Windows (VRPTW) project. Our team has successfully developed a hybrid genetic search algorithm that relies on efficient data structures and algorithms to explore the vast space of possible route configurations. We aim to further enhance the performance of this algorithm by making internal steps more intelligent.
Your Role
You will build upon our open-source implementation of the hybrid genetic search algorithm, PyVRP, and evaluate its performance on large real-world problem instances. Your goal is to maximize the algorithm's efficiency within a short timeframe. You have the freedom to achieve this through parameter optimization, implementing new initialization strategies, or incorporating machine learning to guide internal decisions.
Requirements
- You are a master's 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
As a valued member of our team, you will benefit from:
- Excellent supervision during your graduation project.
- A good internship allowance, laptop, and other office facilities.
- An open, kind, and fun culture.
- Young ORTEC, an association that organizes various activities for juniors, mediors, and graduate students, including Thursday afternoon drinks at our own bar, ORTap.
Next Steps
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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