In the past years, Deep Reinforcement Learning methods integrated with planning methods have been very successful in solving complex Sequential Decision Problems, e.g., in games such as Go. These methods can handle very large state spaces, however, less so large action spaces.
The proposed PhD research project aims to develop new hybrid solution approaches for (stochastic) Sequential Decision Problems with discrete, high-dimensional, and linearly constrained decision spaces as often encountered in Operations Research. To this end, the PhD student will integrate (Deep) Reinforcement Learning methods into traditional Operations Research methods, such as Rolling Horizon approaches using Stochastic Programming. In this way, at the time of decision-making, we combine planning by looking ahead and learning from previous experience. We aim to provide theoretical and empirical results, showing the superiority of the new methods compared to the state of the art in terms of computation at the time of decision-making and the quality of the solution. We will transition from problems with known dynamics to (partly) unknown dynamics. Therefore, we will explore solution strategies that transition from robust optimization to distributionally robust optimization and finally to stochastic optimization.
The PhD student will implement the algorithms and apply them to real-world use cases in Healthcare Logistics, such as multi-appointment scheduling, surgery scheduling, and resource allocation in times of scarce healthcare capacity. Therefore, the PhD student will also be part of the inter-faculty group CHOIR (Centre for Healthcare Operations Improvement and Research). CHOIR is a research center within the UT, and it is currently one of the most active and productive research groups in the field of Operations Research and Management in Healthcare. Through Research, Education, and Valorization, we help healthcare practitioners face their complex logistical challenges.Your profile
Are you interested in this position? Please send your application via the 'Apply now' button below before March 25, 2024 , and include:
For more information regarding this position, you are welcome to contact (Anne Zander, [email protected])About the department
The position will be in the Applied Mathematics department. The Applied Mathematics department has an active research portfolio in stochastic operations research, algorithmic discrete mathematics, complex networks, statistics, systems theory, computational science, and artificial intelligence with applications in health care, energy systems, traffic, and imaging. See MOR and SACS, and MDS for information.
Our research group, Stochastic Operations Research (SOR), conducts mathematical education and research of internationally high standards in the areas of stochastic processes and mathematics of operations research to contribute to the development of mathematics in a multidisciplinary engineering environment and contribute to a better understanding and functioning of our increasingly complex society. See SOR.About the organisation
The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use nowadays, we embrace our role as contributors to a broad range of societal activities and as pioneers of tomorrow's digital society. As part of a people-first tech university that aims to shape society, individuals and connections, our faculty works together intensively with industrial partners and researchers in the Netherlands and abroad, and conducts extensive research for external commissioning parties and funders. Our research has a high profile both in the Netherlands and internationally. It has been accommodated in three multidisciplinary UT research institutes: Mesa+ Institute, TechMed Centre and Digital Society Institute.Want to know more? Zander, A.B. (Anne)
Assistant ProfessorZander, A.B. (Anne)
Do you have questions about this vacancy? Then you can contact Anne for all substantive questions about this position and the application procedure. For general questions about working for the UT, please refer to the chatbot.Contact
Email:[email protected]How to apply Step 1
Apply. When you see a vacancy that appeals to you, you can apply online. We ask you to upload a CV and motivation letter and/or list of publications. You will receive a confirmation of receipt by e-mail.Step 2
Selection. The selection committee will review your application and you will receive a response within 2 weeks after the vacancy has been closed.Step 3
1st interview. The 1st (online or in person) meeting serves as an introduction where we introduce ourselves to you and you to us. You may be asked to give a short presentation. This will be further explained in the invitation.Step 4
2nd interview. In the second interview, we will further discuss the job content, your skills and your talents.Step 5
The offer. If the conversations are positive, you will be made a suitable offer.Your Colleagues
Personal pageOvermars, M.G. (Maik)
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PhD position on Hybrid Methods for Sequential Decision-Making Based on Operation Research and Reinforcement Learning
University of Twente
February 09, 2024
March 25, 2024