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Over the last decade, much attention has been focused on the development of automated letter mail processing systems for postal sorting. Optical character readers and bar-code sorters have begun to augment mechanized processing that has been in use since the mid-1960s. Continuing automated mail processing programs are aimed at minimizing growth in labor costs, which at $30. 5 billion accounted for 83 percent of the total United States Postal Service (USPS) operating costs in fiscal year 1988. Simulation and mixed integer linear programming (MILP) models are developed in this thesis with the objective of assisting postal managers is designing automated systems for the general mail facilities. GMFs) of the USPS. The simulation model utilizes a probabilistic structure to channel processed mail between stations. Processing equipment and associated personnel are modelled as resources. The arrival process can accurately model daily input mail profiles and variability, as well as seasonal loads and secular trends such as changes in mail address quality. Such a detailed probabilistic model provides a realistic test of proposed equipment selections and resources schedules for strategic planning and operations management. A simulation model of a specific medium-sized GMF is constructed using the SLAMII simulation language.