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The efficient scheduling of large mixed parallel applications is challenging. Most existing algorithms utilize scheduling heuristics and approximation algorithms to determine a good schedule as basis for an efficient execution in large scale scientific computing. This paper concentrates on the scheduling of mixed parallel applications represented by task graphs with parallel tasks and precedence constraints between them. Layer-based scheduling algorithms for homogeneous target platforms are improved by adding a move-blocks phase that further reduces the resulting parallel runtime.The layer-based scheduling approach is described and the move-blocks algorithm is introduced in detail. The move-blocks extension provides better scheduling results for small as well as for large problems but has only a small increase in runtime.This is shown by a comparison of the modified and the original algorithms over a wide range of test cases.