for a dynamic variant of a classical combinatorial optimization
problem, namely makespan scheduling. We study the model of a strong
adversary which is allowed to change one job at regular intervals.
Furthermore, we investigate the setting of random changes. Our
results show that randomized local search and a simple evolutionary
algorithm are very effective in dynamically tracking changes made to
the problem instance.
Joint work with Carsten Witt
To appear at IJCAI 2015