A closest vector problem arising in radiation therapy planning
Journal of Combinatorial Optimization
A shortest path-based approach to the multileaf collimator sequencing problem
Discrete Applied Mathematics
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We consider combinatorial optimization problems arising in radiation therapy. Given a matrix I with non-negative integer entries, we seek a decomposition of I as a weighted sum of binary matrices having the consecutive ones property, such that the total sum of the coefficients is minimized. The coefficients are restricted to be non-negative integers. Here, we investigate variants of the problem with additional constraints on the matrices used in the decomposition. Constraints appearing in the application include the interleaf motion and interleaf distance constraints. The former constraint was previously studied by Baatar et al. [Discr Appl Math 152 (2005), 6–34] and Kalinowski [Discr Appl Math 152 (2005), 52–88]. The latter constraint was independently considered by Kumar [Working paper (2007)] in the case where coefficients of the decomposition are not restricted to be integers. For both constraints, we prove that finding an optimal decomposition reduces to finding a maximum value potential in an auxiliary network with integer arc lengths and no negative length cycle. This allows us to simplify and unify the previous approaches. Moreover, we give an O (MN + KM) algorithm to solve the problem under the interleaf distance constraint, where M and N, respectively, denote the number of rows and columns of the matrix I and K is the number of matrices used in the decomposition. We also give an O (MN log M + KM) algorithm for solving the problem under the interleaf motion constraint and hence improve on previous results. Finally, we show the problem can still be solved in O (MN log M + KM) time when both constraints are considered simultaneously. © 2009 Wiley Periodicals, Inc. NETWORKS, 2010