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This paper addresses the problem of trading off between the minimization of program and data memory requirements of single-processer Implementations of dataflow programs. Based on the formal model of synchronous dataflow (SDF) graphs, so called single appearance schedules are known to be program-memory optimal. Among these schedules, buffer memory schedules are investigated and explored based on a two-step approach: 1) an evolutionary algorithm (EA) is applied to efficiently explore the (in general) exponential search space of actor firing orders; 2) for each order, the buffer costs are evaluated by applying a dynamic programming post-optimization step (GDPPO). This iterative approach is compared to existing heuristics for buffer memory optimization.