Abstract.The effect of different representations has been thoroughly analyzed for evolutionary algorithms in stationary environments. However, the role of representations in dynamic environments has been largely neglected so far. In this paper, we empirically compare and analyze three different representations on the basis of a dynamic multi-dimensional knapsack problem. Our results indicate that indirect representations are particularly suitable for the dynamic multi-dimensional knapsack problem, because they implicitly provide a heuristic adaptation mechanism that improves the current solutions after a change.