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We present a framework for capacity allocation decisions for assembly-test (A-T) facilities that is comprised of an optimization model and a simulation model. The optimization and simulation models are used iteratively until a feasible and profitable capacity plan is generated. The models communicate using an automated feedback loop and at each iteration the model parameters are adjusted. We describe the role of the optimization model, the simulation model and the feedback loop. Once the capacity plan is generated, it is passed down to the shop-floor for implementation. Hence, decision makers can develop accurate and more profitable execution level capacity plans using the integrated model which utilizes both optimization and simulation models. In this paper, we focus on the optimization model for capacity planning for the entire A-T facility at the individual equipment (resource) level for a two-week planning period and briefly discuss the simulation and the adjustment model.