Freeway ramp control has been successfully implemented since the mid-1960s as an efficient and viable freeway management strategy. However, the effectiveness of any ramp control strategy is largely dependent on site-specific customization and calibration, preferably before its deployment. A general methodology for such performance optimization of ramp control strategies is proposed in a microscopic simulation environment as an alternative to trial-and-error field experimentation. The applicability of the methodology is demonstrated by implementation on Minnesota's new stratified zone metering (SZM). Further, the effect of external factors, such as traffic demand variation and incidents, on SZM control and optimization results was also studied. Results show that the optimization methodology is highly effective depending on the optimization objective, test site characteristics, and demand levels.