A data-driven heuristic decision strategy for data-scarce optimization: with an application towards bio-based composites

Algorithmic optimization is a viable tool for solving complex materials engineering issues. In this study, a data-scarce Bayesian optimization model was developed to research the composition of bio-based composites. The proof-of-concept program adjusts the natural materials' weight ratios to optimize towards user-defined mechanical properties....

Automated dig-limit optimization through simulated annealing

Multi-robot parcel sorting systems: Allocation and path finding

The logistics industry is being modernized using information technology and robots. This change encompasses a new set of challenges in warehouses. Recently, some companies have started using robot fleets to sort products and parcels. This thesis studies those systems, and researches the combinatorial problems that arise within them. Three main...

Optimizing truck driver schedules with dependent working shifts, drivers' legislation, and multiple time windows

In logistics, minimizing the resource expenses can be done by minimizing the total number of hours that each truck driver has to work. This sum of working hours is referred to as the total schedule duration for all truck drivers. Minimizing this total schedule duration is the main goal in the optimization problem that we consider. The considered...