Modelling and strong linear programs for mixed integer programming
Algorithms and model formulations in mathematical programming
A new optimization algorithm for the vehicle routing problem with time windows
Operations Research
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Solving binary cutting stock problems by column generation and branch-and-bound
Computational Optimization and Applications
An Optimization Based Heuristic for Political Districting
Management Science
Developing a national allocation model for cadaveric kidneys
Proceedings of the 32nd conference on Winter simulation
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Flight String Models for Aircraft Fleeting and Routing
Transportation Science
Dynamic Allocation of Kidneys to Candidates on the Transplant Waiting List
Operations Research
The Optimal Timing of Living-Donor Liver Transplantation
Management Science
Patient Choice in Kidney Allocation: A Sequential Stochastic Assignment Model
Operations Research
Selected Topics in Column Generation
Operations Research
An Exact Method for Balancing Efficiency and Equity in the Liver Allocation Hierarchy
INFORMS Journal on Computing
A Broader View of Designing the Liver Allocation System
Operations Research
Commentaries to “The Vital Role of Operations Analysis in Improving Healthcare Delivery”
Manufacturing & Service Operations Management
Optimizing the facility location design of organ transplant centers
Decision Support Systems
Hi-index | 0.02 |
Cadaveric liver transplantation is the only viable therapy for end-stage liver disease patients without a living donor. However, this type of transplantation is hindered in the United States by donor scarcity and rapid viability decay. Given these difficulties, the current U.S. liver allocation policy balances allocation likelihood and geographic proximity by allocating cadaveric livers hierarchically. We consider the problem of maximizing the efficiency of intraregional transplants through the redesign of liver allocation regions. We formulate the problem as a set partitioning problem that clusters organ procurement organizations into regions. We develop an estimate of viability-adjusted intraregional transplants to capture the trade-off between large and small regions. We utilize branch and price because the set partitioning formulation includes too many potential regions to handle explicitly. We formulate the pricing problem as a mixed-integer program and design a geographic-decomposition heuristic to generate promising columns quickly. Because the optimal solution depends on the design of geographic decomposition, we develop an iterative procedure that integrates branch and price with local search to alleviate this dependency. Finally, we present computational studies that show the benefit of region redesign and the efficacy of our solution approach. Our carefully calibrated test instances can be solved within a reasonable amount of time, and the resulting region designs yield a noticeable improvement over the current configuration.