The design of public storage warehouses needs to fit market segments to increase the average revenue in an environment of high demand. This paper presents a revenue model integrated with queuing and price-demand theories to solve the design and pricing problem for public storage warehouses. We consider two demand cases in the model, which are exponential demand and piecewise linear demand. We also develop a solution based on dynamic programming techniques to solve the problem. Using data from a warehouse, we conduct numerical experiments. Results show that our approach can improve the expected revenue of public storage warehouses with high demand by 16.6% on average. We further conduct sensitivity analysis on price, and investigate the relation between revenue and price.