Attributes of Dynamic Combinatorial

Abstract. The field of evolutionary computation has traditionally fo-cused on static optimisation problems but recently, many new approaches have been proposed that adapt traditional evolutionary algorithms to deal with the task of tracking high-quality solutions as the search space changes over time. Algorithms developed specifically for dynamic do-mains have been tested on a wide range of different problems, including well-specified benchmark generators. However, the lack of theoretical re-sults, a general omission of references to actual real-world scenarios, as well as a substantial emphasis on the continuous domain may divert at-tention away from some highly relevant issues. Here we review the state of the field and analyse dynamics in the combinatorial domain, using the subset sum problem as an example. It is shown that some of the assump-tions underlying the development of new algorithms do not necessarily hold in the case of discrete optimisation. Furthermore, it is argued that more attention should be paid to the underlying dynamics and the im-pact of the representation used.