A new approach to simulation response optimization is presented that takes advantage of the ability to run simultaneous replications of different experimental factor settings in a single run. It is also possible to use different time scales for the events corresponding to different design points. In this manner, the run can focus on factor settings that are likely to be optimal and feasible. An example is presented using a penalty function to dilate event times to find the cycle-time constrained capacity of a queue.