Optimize Hybrid Genetic Search for Vehicle Routing
6 dagen 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, winning the DIMACS 2022 challenge. We aim to further enhance its capabilities by making internal steps more intelligent.
Your Challenge
You will build upon PyVRP, an open-source implementation of the hybrid genetic search algorithm. Your task will be to evaluate PyVRP on large real-world problem instances and push its limits to maximize performance in a short amount of time. You will have the freedom to achieve this goal through various means, such as optimizing parameters, implementing additional initialization strategies, or using machine learning to guide internal decisions.
Requirements
- You are a master student in computer science, operations research, or artificial intelligence.
- You are comfortable with Python and have experience with optimization algorithms.
- Experience with compiled languages like C++ and/or running computational jobs on (cloud) compute infrastructure is a plus.
- You are currently living in the Netherlands and studying at a Dutch University.
- You communicate fluently in English, verbally and in writing.
- You are available for 6 months for 32-40 hours a week.
What We Offer
- Entrance to a company that shares a drive to use problem-solving skills to improve our planet.
- Inclusion in a company that fosters its students through excellent supervision, good internship allowance, laptop, and other office facilities.
- An open, kind, and fun culture.
Did we spark your interest? Then 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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