Optimization under uncertainty

Safety-critical settings sometimes require optimization with respect to the worst-case realization of the problem setting. The adversarial, robust optimization setting is especially useful when errors are very costly.
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Explainable optimization

Optimization solvers are often unexplainable black boxes where the reasoning for a solution is inaccessible to users. We use argumentation to empower the interaction between optimization solvers and users, supported by tractable explanations which certify or refute solutions.
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Scheduling & rescheduling

In logistics applications such as our Royal Mail collaboration, a planned schedule is made in advance. But suppose something disruptive happens and we need to adapt quickly. How can we make rescheduling efficient?
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Designing heat recovery networks

Heat exchanger networks reuse excess industrial process heat onsite and thereby improve energy recovery. We consider the resulting mixed-integer nonlinear optimization problem for designing heat recovery networks.
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Bioprocess optimization for stem cell tissue engineering

This project considers robust superstructure design and operation of a bioreactor that produces red blood cells. Although we develop an optimization model for a specific bioreactor, the intellectual framework may generally apply to bioprocess optimization.
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