Peter Brucker

TL;DR: Neighborhoods are derived which generalize the block-approach based neighborhoods which have been successfully applied to noncyclic job-shop problems, and for a variant of this neighborhood opt-connectivity is proved.

TL;DR: Crew or staff scheduling is a complex combinatorial problem which consists of assigning tasks to persons which have to perform these task and to schedule the performance of the tasks.

TL;DR: The problem of scheduling G groups of jobs on m parallel machines is considered and a family of approximation algorithms is constructed, showing the problem to be NP-hard even for the case of two identical machines, unit processing times, unit set-up times and a common deadline.

TL;DR: A fast and efficient head–tail adjustment algorithm is presented for the job-shop scheduling problem to improve lower and upper bounds, and to prove the optimality of solutions for benchmark problems which have been open for some time.