Robust and cost-effective distribution is critical to any home delivery network growing company, both to meet demand under normal conditions and to adapt to temporary disruptions. Home healthcare is anticipated to be ...Robust and cost-effective distribution is critical to any home delivery network growing company, both to meet demand under normal conditions and to adapt to temporary disruptions. Home healthcare is anticipated to be a rapidly growing modality of healthcare, itself the largest industry in the US and rife with optimization needs in areas such as logistics, scheduling, and supply chains. We develop two mixed integer programming models to optimize forward storage locations in the supply chain of a national consumable medical supplies company with consistent monthly repeating demand, temporary disruption of facility operations, and remote international manufacturers. Modified p-median single and multi-echelon models are used to determine optimal locations of warehouses and distribution facilities that minimize total transportation cost, with 13% savings in one application (approximately $1.4 million annually). Sensitivity analyses to a range of scenarios suggest that the optimal solution is robust across a number of potential scenarios.展开更多
文摘Robust and cost-effective distribution is critical to any home delivery network growing company, both to meet demand under normal conditions and to adapt to temporary disruptions. Home healthcare is anticipated to be a rapidly growing modality of healthcare, itself the largest industry in the US and rife with optimization needs in areas such as logistics, scheduling, and supply chains. We develop two mixed integer programming models to optimize forward storage locations in the supply chain of a national consumable medical supplies company with consistent monthly repeating demand, temporary disruption of facility operations, and remote international manufacturers. Modified p-median single and multi-echelon models are used to determine optimal locations of warehouses and distribution facilities that minimize total transportation cost, with 13% savings in one application (approximately $1.4 million annually). Sensitivity analyses to a range of scenarios suggest that the optimal solution is robust across a number of potential scenarios.
