Thesis supervisor: Máté Hegyháti
Location of studies (in Hungarian): Széchenyi István University Abbreviation of location of studies: SZE
Description of the research topic:
The scheduling problems appearing in real life are often not deterministic and offline. There are different ways of addressing uncertainties in scheduling. One option is to quickly alter the planned schedule in case any kind of unexpected event occurs. Since these problems are already NP-hard in the offline case, it is a challenging task to provide a good answer in reasonable time.
The job of the PhD candidate is to design and implement a software framework which applies both theoretical advancements and modern development techniques in order to provide quick and valuable answers to such scheduling questions.
Requirements:
• Background in programming, and software design
• Good understanding of the principles of discrete optimization
• Fluent English
Preferred qualities:
• Former experience with any kind of optimization
• Engineering, logistics experience on any relevant fields
• Advanced C++ skills
• Former research on a related topic
Experience with Neural networks, Artificial Intelligence techniques, Evolutionary algorithms