This research tackles a common subset of the multiple facility location problem; where location groupings referred to as “circuits” are assigned to facilities, the sets of demand and potential facility locations are the same, and the demand at each location is sole-sourced. This problem, henceforth termed as the circuitization problem, is applicable in a variety of situations, particularly service provision, goods transportation, and supply chain distribution [1] [2].The usual optimization solution method for the facility location problem is mixed integer linear programming. However, there are many difficulties in applying MILP, including the cost of acquiring optimization software and modeling the dozens to thousands of variables and constraints involved. Since IP problems are NP-hard, the computing time for optimizing solutions to large problems becomes prohibitive.A satisficing heuristic model was therefore developed, which classifies the demand locations according to size, and assigns facilities using decision rules designed to balance the competing objectives of minimizing setup costs while minimizing travel costs for customers, taking into consideration demand and capacity constraints.Applying the heuristic to the municipal court system of the province of Nueva Ecija in the Philippines resulted in a scheme with costs lower than that of the current system by PhP48.7 million. Further research will focus on the comparison of the heuristic with MILP optimization algorithms.