Organ transplants are essential for many end-stage organic disease patients. Unfortunately, because of medical or biological incompatibilities, not all donors can donate to their intended recipients. These incompatibilities can be overcome by organ exchange programs, which find new compatible donor–patient pairs by exchanging donors between patients. Organ exchange programs have become prevalent in the last decade for kidneys, and liver exchanges have also been increasing steadily. However, despite the growing number of liver exchanges, since the procedure is relatively new, there is a lack of studies attempting to optimize exchange plans through mathematical programming. This paper develops a new integer programming model for liver exchange programs that takes into account the unique characteristics of liver transplantation. In addition, a new enhanced model is obtained by applying the reformulation-linearization technique (RLT), which provides tight linear programming (LP) relaxation bounds and is computationally efficient.
Bibliographical noteFunding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korean government (Ministry of Science, ICT & Future Planning) (No. NRF-2015R1C1A1A02036682 ) and the Ministry of Education (No. NRF-2018R1D1A1B07047651 ) and also supported by Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea government (MOTIE) ( P0008691 , The Competency Development Program for Industry Specialist).
- Integer programming
- Liver exchange program
- OR in health services
- Reformulation-linearization technique
ASJC Scopus subject areas
- Computer Science Applications
- Artificial Intelligence