A note on improving the performance of approximation algorithms for radiation therapy

The segment minimization problem consists of representing an integer matrix as the sum of the fewest number of integer matrices each of which have the property that the non-zeroes in each row are consecutive. This has direct applications to an effective form of cancer treatment. Using several insights, we extend previous results to obtain constant-factor improvements in the approximation guarantees. We show that these improvements yield better performance by providing an experimental evaluation of all known approximation algorithms using both synthetic and real-world clinical data. Our algorithms are superior for 76% of instances and we argue for their utility alongside the heuristic approaches used in practice.

• Type: Journal
• Year: 2011
• Where: IPL
• Authors: Therese C. Biedl, Stephane Durocher, Holger H. Hoos, Shuang Luan, Jared Saia, Maxwell Young
• Keywords: Integer Matrices, IPL 2011, Real-world Clinical Data, Segment Minimization Problem