The idea of decomposed software pipelining is to decouple the software pipelining problem into a cyclic scheduling problem without resource constraints and an acyclic scheduling problem with resource constraints. In terms of loop transformation and code motion, the technique can be formulated as a combination of loop shifting and loop compaction. Loop shifting amounts to move statements between iterations thereby changing some loop independent dependences into loop carried dependences and vice versa. Then, loop compaction schedules the body of the loop considering only loop independent dependences, but taking into account the details of the target architecture. In this paper, we show how loop shifting can be optimized so as to minimize both the length of the critical path and the number of dependences for loop compaction. Both problems (and the combination) are polynomially solvable with fast graph algorithms, the first one by using an algorithm due to Leiserson and Saxe, the second one by designing a variant of minimum-cost flow algorithms.