Inverse radiation therapy planning: a multiple objective optimization approach
Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
Decomposition of integer matrices and multileaf collimator sequencing
Discrete Applied Mathematics
How to decompose a binary matrix into three hv-convex polyominoes
DGCI'13 Proceedings of the 17th IAPR international conference on Discrete Geometry for Computer Imagery
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Motivated by Intensity Modulated Radiation Therapy, we consider the problem of the minimum decomposition of an integer matrix into hv-convex matrices with time and cardinality objectives. We study the special case where the matrix to decompose is a binary matrix (in this case, time decomposition and cardinality decomposition are the same). We prove that the decomposition into two hv-convex matrices or into two hv-convex polyominoes is polynomially solvable. For the decomposition into three hv-convex matrices the problem becomes NP-complete.