The most common near-term approach to upgrading railway corridors to achieve high speeds is by incremental improvement. Existing infrastructure or rolling stock can be improved in various ways to allow for increasing speeds and reducing travel time along a route. Each track section has a characteristic set of opportunities for increasing speed and their corresponding effects on travel time reduction, along with an associated set of costs. Similarly, each type of rolling stock has the potential to increase operational speed and reduce travel time, corresponding to a specific price tag. This research focuses on developing a decision support process by using mathematical programming to identify the most cost-effective strategy for reducing corridor travel time given a prescribed performance goal and budget. This optimization process was implemented in a railway corridor in Taiwan, and the result showed that the best strategy was a combination of infrastructure upgrade and rolling stock acquisition. Using this tool can help states and railway agencies simultaneously maximize capital investment returns and maintain reliable services for their customers.