The Eindhoven University of Technology is looking for a PhD candidate with a background in Industrial Engineering, (Applied) Mathematics, Operations Research, Econometrics, Artificial Intelligence, or Operations Management, interested in rigorous research with practical relevance of sustainable and smart logistics.
This project aims to investigate these different collaboration scenarios between actors in the chain.
Table of Contents
Scholarship Sponsor | Eindhoven University of Technology |
Scholarships level | PhD Position |
Award Amount | Salary |
Fellowship Period | Four years |
Study area | Mathematics |
Opening date | February 24, 2021 |
Closing date | March 15, 2021 |
Today’s transportation systems, facilitating the movement of goods in our supply chains, are facing several challenges in the form of environmental concerns but also through changes in policy, infrastructure and shifts in consumer demands. Transportation systems and the related logistics processes need to be more flexible to adjust to this dynamic environment while, at the same time, improving the associated environmental footprint to achieve the goal of zero-emission transport. A way to realize this is by transforming current transportation networks towards smart systems in which actors make more informed and coordinated decisions while sharing tasks and resources.
This transformation, however, requires the collaboration of different actors in the chain to encourage resource sharing and reach reasonable solutions to complex decision problems that benefit all parties involved. This includes both horizontal and vertical collaboration in routing settings and the sharing of available storage space at transport hubs and intermediary depots. To facilitate such collaborative environments, it is essential to introduce financial allocation rules that divide costs and benefits in a fairway.
To identify fair allocation and align incentives between actors, you will make use of cooperative game theory. In this theory, an important question is how to allocate an amount of money amongst a collaborating group of players (e.g., actors in a transport network). A well-known and fair solution concept for answering this question is the core. The core is the set of all allocations that divides the money so that no individual player or group of players is worse off.
In the project, you will formulate several transportation-oriented cooperative games and introduce several associated allocation rules. After that, you will investigate whether these allocation rules’ allocations belong to the core (i.e., investigate whether the shares are fair).
Checking whether a portion belongs to the body is difficult, as it requires solving a transportation problem per subgroup of players –and the number of subgroups of players is exponential in the number of players. To deal with this computational complexity, you make use of data-driven algorithms and machine learning (ML) techniques that can help to discover underlying patterns within our problem environments and identify reasonable solutions within limited computational time.
You, as a successful applicant, will perform the PhD project outlined above. The research will be concluded with a PhD thesis. Dr Loe Schlicher and dr will supervise you. Sonja Rohmer. A small teaching load is part of the job.
You will be part of the Operations Planning, Accounting & Control group (OPAC). OPAC currently consists of 25 staff members, ten postdocs and 30 PhD students. The faculty teaches and conducts research in operations planning and control in manufacturing, maintenance services, logistics and supply chains. An analysis is generally quantitative, while many of the researchers also engage in empirical research.
The OPAC group is responsible for all teaching in the areas of operations management, transportation, manufacturing operations, reliability and maintenance, and accounting and finance, both at undergraduate and graduate level. The OPAC group has close collaborations with the industry, which gives direct access to challenging operations management problems, new technologies, and empirical data.
The deadline for applications is March 15, 2021
Do you recognize yourself in this profile and would you like to know more? Please contact Loe Schlicher, l.p.j.schlicher[at]tue.nl or Sonja Rohmer s.u.k.rohmer[at]tue.nl.
For information about terms of employment, please contact Susan Opgenoorth, s.g.j.opgenoorth[at]tue.nl.
Please visit www.tue.nl/jobs to find out more about working at TU/e!
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