Dynamic string‐averaging CQ‐methods for the split feasibility problem with percentage violation constraints arising in radiation therapy treatment planning. (30th December 2020)

• Record Type: Journal Article
• Authors: Brooke, Mark; Censor, Yair; Gibali, Aviv
• Other Names: Viana Ana guestEditor.; Marques Inês guestEditor.; Dias Joana Matos guestEditor.
• Is Part Of: International transactions in operational research. Volume 30:Number 1(2023)
• Page Start: 181
• Page End: 205
• Publication Date: 2020-12-30
• Subjects: string‐averaging -- CQ‐algorithm -- split feasibility -- percentage violation constraints -- radiation therapy treatment planning -- dose‐volume constraints -- common fixed points -- cutter operator; Operations research -- Periodicals; 003
• DOI: 10.1111/itor.12929
• Languages: English
• ISSNs: 0969-6016

Abstract

Abstract: We study a feasibility‐seeking problem with percentage violation constraints (PVCs). These are additional constraints that are appended to an existing family of constraints, which single out certain subsets of the existing constraints and declare that up to a specified fraction of the number of constraints in each subset is allowed to be violated by up to a specified percentage of the existing bounds. Our motivation to investigate problems with PVCs comes from the field of radiation therapy treatment planning (RTTP) wherein the fully discretized inverse planning problem is formulated as a split feasibility problem and the PVCs give rise to nonconvex constraints. Following the CQ algorithm of Byrne (2002, Inverse Problems, Vol. 18, pp. 441–53), we develop a string‐averaging CQ‐method that uses only projections onto the individual sets that are half‐spaces represented by linear inequalities. The question of extending our theoretical results to the nonconvex sets case is still open. We describe how our results apply to RTTP and provide a numerical example.