This paper deals with the performance optimization of multiple-task applications in GRID environments. Typically such applications are launched by a Resource Manager, which only takes into account the application's resource requirements and current availability on the GRID. Here a novel approach is presented, that performs resource management in user space, making it possible to exploit application modularity and flexibility and to take into account expected performance figures produced by GRID simulation. The objective is to make optimized choices that can lead to