PhD Position Optimizing Multi-actor Transport and Logistics Systems

Would you like to develop new theory and algorithms for problems with multiple interacting actors? Are you interested in working at the intersection of game theory and mixed-integer optimisation?

Transport and logistics systems consist of many players with potentially conflicting objectives that continuously strive to maximize their performance. The competition and collaboration between these players can influence their decision-making, which is something that traditional Mixed Integer Linear Programming (MILP) formulations with a single decision-maker cannot capture. The goal of this PhD is to develop novel methodologies at the intersection of operations research and game theory to address these problems.

Applications can go beyond the transport and logistics domain.

Your research will focus on mathematical modelling and algorithm development for planning and operating multi-actor systems, taking into account that the actions of one actor influence the opportunities and performance of others. A central methodological component of the position is the development of scalable optimisation algorithms for large and computationally challenging problem instances. You will formulate mathematical programming models and design solution approaches based on techniques such as column generation, branch-and-price, and Benders decomposition.

You will be expected to:

• design scalable solution methods for large-scale optimisation problems;
• contribute to scientific publications in leading journals in operations research, transportation, and logistics;
• communicate research findings to an interdisciplinary audience.

You will join the Transport and Logistics section of the Department of Engineering Systems and Services

• We are looking for a candidate who meets the following requirements:
• An MSc degree in operations research, econometrics, applied mathematics, computer science, industrial engineering, systems and control, or a closely related discipline.
• A strong background and demonstrated experience in mathematical optimisation, in particular mixed-integer programming.
• Excellent programming skills (e.g., Python, Julia, Java, or C++) and experience with optimization solvers.
• Very good academic writing and communication skills in English.
• An open and collaborative attitude and the ability to work effectively in an interdisciplinary and international research environment.
• Knowledge of game theory, bi-level optimization and decomposition-based solution algorithms are a plus.

Working at TU Delft means contributing to solutions that really make a difference.

For over 180 years, we have been training engineers who make an impact worldwide in companies, government bodies, or as entrepreneurs. Our alumni turn knowledge into concrete solutions for the challenges of today and tomorrow.

These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.

Working at TU Delft means join an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology,society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, socialorganisationsand governments.

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an…