Dynamic optimization problems (DOPs) are an underrepresented class in benchmarking evolutionary computation systems (ECS). Most benchmarks focus on more or less expensive problems, but which never change during the optimization. In real-world logistics operations however, dynamic changes and even uncertainty are natural and have to be dealt with. While evolutionary algorithms are certainly well suited methods to tackle such problems, the field lacks public and open source, easy-to-use, but still complex dynamic en…