Kunter Seref Akbay

GE Plastics Optimizes the Two-Echelon Global Fulfillment Network at Its High Performance Polymers Division

To achieve the highest customer satisfaction at the lowest costs, GE Plastics adopted a global approach to its manufacturing operations. Previously it met demand in one geographic region with production from that region only. It developed a decision-support system (DSS) to optimize the two-echelon global manufacturing supply chain for its high performance polymers division. The DSS uses a math-programming model to maximize contribution margin while taking into consideration product demands and prices, plant capacities, production costs, distribution costs, and raw material costs. The results of the model are the optimal production quantities by plant and the total contribution margin. The DSS is implemented in Excel and uses LINGO to solve the optimization model. After successfully implementing this system at the high performance polymers division, GE Plastics is rolling it out to other divisions.

Automated Bed Assignments in a Complex and Dynamic Hospital Environment

Bed management, an important function of any hospital, has a major impact on patient care, patient flow, patient and staff satisfaction, and ultimately on the hospitals operating margin. A key challenge in bed management is optimizing the bed-assignment process in a complex and dynamic operating environment. Efficient bed assignment requires the merging of clinical information, hospital operations information, interdependencies between units, and real-time information on patients, resources, and workflows. We have developed analytical decision support tools with embedded mathematical models to periodically recommend bed-patient assignments. Using an innovative mixed-integer goal-programming modeling approach, we are able to accommodate the multiple goals and complex operating rules of different hospitals. We implemented and hosted our prototype bed-assignment solution as a cloud-based application for Mount Sinai Medical Center in New York.