We consider force-majeure supply disruptions in a dynamic, multi-product manufacturing supply chain with time-dependent parameters. We present a linear programming model that captures a specific force-majeure scenario with respect to several objective functions that can be combined in a...

Reinforcement learning (RL) algorithms have proven to be useful tools for combinatorial optimisation. However, they are still underutilised in facility layout problems (FLPs). At the same time, RL research relies on standardised benchmarks such as the Arcade Learning Environment. To address...

Much of energy economics curricula involves the study of techno-economic aspects of energy systems with an increasing focus devoted to fostering an understanding of the interactions between innovative technologies and adaptive markets. As the interplay of these dynamics and their impacts on...

As conventional last-mile transport contributes to traffic congestion and pollution, urban areas need new approaches to transporting freight. One promising idea is integrating freight deliveries with existing public transport infrastructures like light rail. However, this concept creates the...

One promise of computational decision support is enabling better solutions in interactions and social exchange by supporting human strengths (e.g. intuitive decision-making) with formal procedures. This study investigates whether mathematical post-negotiation procedures can guide parties to an...

Globally optimal free flight trajectory optimization can be achieved with a combination of discrete and continuous optimization. A key requirement is that Newton's method for continuous optimization converges in a sufficiently large neighborhood around a minimizer. We show in this paper that,...

The optimization of periodic timetables is an indispensable planning task in public transport. Although the periodic event scheduling problem (PESP) provides an elegant mathematical formulation of the periodic timetabling problem that led to many insights for primal heuristics, it is notoriously...