[1. Bortfeld T. IMRT: a review and preview. Phys Med Biol. 2006;51(13):R363-R379.10.1088/0031-9155/51/13/R2116790913]Search in Google Scholar
[2. Hatano K, Araki A, Sakai M, et al. Current status of intensity-modulated radiation therapy (IMRT). Int J Clin Oncol. 2007;12(6):408-415.10.1007/s10147-007-0703-918071859]Search in Google Scholar
[3. Yu CX, Amies CJ, Svatos M. Planning and delivery of intensity-modulated radiation therapy. Med Phys. 2008:35(12):5233-5241.10.1118/1.300230519175082]Search in Google Scholar
[4. Shepard DM, Ferris MC, Olivera GH, et al. Optimizing and delivery of radiation therapy to cancer patients. Siam Review. 1999:41(4):721-744.10.1137/S0036144598342032]Search in Google Scholar
[5. Lim J, Ferris MC, Wright SJ, et al. An optimization framework for conformal radiation treatment planning. INFORMS J Comput. 2007;19(3):366-380.10.1287/ijoc.1060.0179]Search in Google Scholar
[6. Morrill SM, Lane RG, Wong JA, et al. Dose-volume considerations with linear programming optimization. Med Phys. 1991;18(6):1201-1210.10.1118/1.5965921753905]Search in Google Scholar
[7. Breedveld S, Storchi PRM, Keijzer M, et al. Fast, multiple optimizations of quadratic dose objective functions in IMRT. Phys Med Biol. 2006;51(14):3569-3579.10.1088/0031-9155/51/14/01916825749]Search in Google Scholar
[8. Censor Y, Ben-Israel A, Xiao Y, et al. On linear infeasibility arising in intensity-modulated radiation therapy inverse planning. Linear Algebr Appl. 2008;428(5-6):1406-1420.10.1016/j.laa.2007.11.001270171319562040]Search in Google Scholar
[9. Rosen II, Lane RG, Morrill SM, et al. Treatment plan optimization using linear programming. Med Phys. 1991;18(2):141-152.10.1118/1.5967002046598]Search in Google Scholar
[10. Allen H. Designing radiotherapy plans with elastic constraints and interior point methods. Health Care Manag Sci. 2003;6(1):5-16.10.1023/A:1021970819104]Search in Google Scholar
[11. Bortfeld T, Bürkelbach J, Boesecke R, et al. Methods of image reconstruction from projections applied to conformation radiotherapy. Phys Med Biol. 1990;35(10):1423-1434.10.1088/0031-9155/35/10/007]Search in Google Scholar
[12. Xing L, Hamilton RJ, Spelbring D, et al. Fast iterative algorithms for three-dimensional inverse treatment planning. Med Phys. 1998:25(10):1845-1849.10.1118/1.598374]Search in Google Scholar
[13. Xing L, Chen GTY. Iterative methods for inverse treatment planning. Phys Med Biol. 1996:41(10):2107-2123.10.1088/0031-9155/41/10/018]Search in Google Scholar
[14. Aleman DM, Mišić VV, Sharpe MB. Computational enhancements to fluence map optimization for total marrow irradiation using IMRT. Comput Oper Res. 2013;40(9):2167-2177.10.1016/j.cor.2011.05.028]Search in Google Scholar
[15. Aleman DM, Glaser D, Romeijn HE, et al. Interior point algorithms: guaranteed optimality for fluence map optimization IMRT. Phys Med Biol. 2010;55(18):5467-5482.10.1088/0031-9155/55/18/013]Search in Google Scholar
[16. Oskoorouchi MR, Ghaffari HR, Terlaky T, et al. An interior point constraint generation algorithm for semi-infinite optimization with health-care application. Oper Res. 2011;59(5):1184–1197.10.1287/opre.1110.0951]Search in Google Scholar
[17. Hamacher KK, Küfer K-H. Inverse radiation therapy planning—a multiple objective optimization approach. Discrete Appl Math. 2002;118(1):145-161.10.1016/S0166-218X(01)00261-X]Search in Google Scholar
[18. Halabi T, Craft D, Bortfeld T. Dose-volume objectives in multi-criteria optimization. Phys Med Biol. 2006;51(15):3809-3818.10.1088/0031-9155/51/15/01416861782]Search in Google Scholar
[19. Deasy JO. Multiple local minima in radiotherapy optimization problems with dose-volume constraints. Med Phys. 1997:24(7):1157-1161.10.1118/1.5980179243478]Search in Google Scholar
[20. Wu C, Jeraj R, Mackie TR. The method of intercepts in parameter space for the analysis of local minima caused by dose-volume constraints. Phys Med Biol. 2003;48(11):149-157.10.1088/0031-9155/48/11/40212817946]Search in Google Scholar
[21. Wu Q, Mohan R. Multiple local minima in IMRT optimization based on dose-volume criteria. Med Phys. 2002;29(7):1514-1527.10.1118/1.148505912148734]Search in Google Scholar
[22. Romeijn HE, Ahuja RA, Dempsey JF, et al. A new linear programming approach to radiation therapy treatment planning problems. Oper Res. 2006;54(2):201-216.10.1287/opre.1050.0261]Search in Google Scholar
[23. Zhang Y, Merritt M. Dose–volume-based IMRT fluence optimization: a fast least-squares approach with differentiability. Linear Algebr Appl. 2008;428(5-6):1365-1387.10.1016/j.laa.2007.09.037]Search in Google Scholar
[24. Spirou SV, Chui CS. A gradient inverse planning algorithm with dose-volume constraints. Med Phys. 1998:25(3): 321-333.10.1118/1.5982029547499]Search in Google Scholar
[25. Cotrutz C, Xing L. Using voxel-dependent importance factors for interactive DVH-based dose optimization. Phys Med Biol. 2002:47(10):1659-1669.10.1088/0031-9155/47/10/30412069085]Search in Google Scholar
[26. Yang Y, Xing L. Inverse treatment planning with adaptively evolving voxel-dependent penalty scheme. Med Phys. 2004;31(10):2839-2844.10.1118/1.179931115543792]Search in Google Scholar
[27. Shou Z, Yang Y, Cotrutz C, et al. Quantification of the a priori dosimetric capabilities of spatial points in inverse planning and its significant implication in defining IMRT solution space. Phys Med Biol. 2005;(7):1469-1482.10.1088/0031-9155/50/7/01015798337]Search in Google Scholar
[28. Zhaosong Lu, Zhang Y. Penalty decomposition methods for l0-norm minimization. arXiv preprint, arXiv:1008.53722, 2010.]Search in Google Scholar
[29. Craft D, Bangert M, Long T, et al. Shared data for intensity modulated radiation therapy (IMRT) optimization research: the CORT dataset. GigaScience. 2014;3(1):2047–217X–3–37.10.1186/2047-217X-3-37432620725678961]Search in Google Scholar
[30. Schmidt M, Berg E, Friedlander M, et al. Optimizing costly functions with simple constraints: A limited-memory projected quasi-newton algorithm. In: Proceedings of the Twelth International Conference on Artificial Intelligence and Statistics Artificial Intelligence and Statistics. 2009. pp. 456-463]Search in Google Scholar
[31. Schmidt M. minConf: Projection methods for optimization with simple constraints in Matlab. 2008. [Online]. Available: http://www.cs.ubc.ca/~schmidtm/Software/minConf.html.]Search in Google Scholar
[32. Grant M. Boyd S. CVX: Matlab software for disciplined convex programming,version 2.1. 2014. [Online]. Available: http://cvxr.com/cvx.]Search in Google Scholar