With Generalized Processor Sharing (GPS), packets of different applications are backlogged in different queues and the different queues are served according to predetermined weights. It is well-established that GPS is a viable approach to provide different QoS for different applications. However, since the analysis of systems with GPS is a notoriously hard problem, it is not easy to find the weights that optimize GPS for some given objective function. The latter is important from a practical point of view. In this paper, we assume the objective function to be some weighted combination of (non-linear) increasing functions of the mean delays. We use results from strict priority scheduling (which can be regarded as a special case of GPS) to establish some exact theoretical bounds on when GPS is more optimal than strict priority. Some important case studies are included, thereby resorting to Monte-Carlo estimation to find the optimal weights for GPS systems.