This paper discusses optimization of the Capacitated Facility Location Problem (CFLP) under uncertainty in demand and supply. This research proposes an optimization framework that addresses the capacitated facility location problem by considering delivery companies to identify optimal warehouse locations so that orders are met at the lowest cost depending on warehouse capacity.  This research was applied to the cities of the Kingdom of Saudi Arabia with high demand for delivery; therefore, census data were taken in the cities available for study, and a small proportion of each city was customers.  A novel mixed integer linear programming was proposed and solved by Python to obtain the minimum total transportation and fixed costs for warehouse construction. The proposed warehouse sites were presented on a map, and each city was connected to its optimal warehouse.