Sequential modeling and optimization for resources in mail-order pharmacy automation systems

This research proposes a resource planning tool for minimizing the total operational costs of Mail-order Pharmacy Automation (MOPA) systems. The MOPA system is a make-to-order manufacturing system that typically uses auto-dispensing machines to fill large volumes of prescription orders. The objective of resource planning is to determine the optimal number of dispensers, canisters, and replenishment operators. In this research, two mixed integer linear programming models are proposed and solved sequentially to minimize dispenser assignment and labor costs. The first model addresses dispenser planning and planogram optimization to determine the optimal number and location of dispensers for each medication, while the second model is used to determine the number and types of canisters needed for each dispenser and the number of cart and replenishment operators. Experimental results helped with understanding the factors that influence MOPA system resource planning.