Comparison of mixed integer programming and fast simulated annealing for optimizing beam weights in radiation therapy

被引:37
作者
Langer, M [1 ]
Morrill, S [1 ]
Brown, R [1 ]
Lee, O [1 ]
Lane, R [1 ]
机构
[1] ONE STONE CORP,CAMBRIDGE,MA 02140
关键词
radiation therapy planning; optimization; mixed integer programming; simulated annealing; dose-volume limits;
D O I
10.1118/1.597857
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Two competing methods for assigning intensities to radiation treatment beams were tested. One method was derived from mixed integer programming and the other was based on simulated annealing. The methods faced a common objective and identical constraints. The goal was to maximize the minimum tumor dose while keeping the dose in required fractions of normal organ volumes below a threshold for damage. The minimum tumor doses of the two methods were compared when all the dose-volume constraints were satisfied. A mixed integer linear program gave a minimum tumor dose that was at least 1.8 Gy higher than that given by simulated annealing in 7 of 19 trials. The difference was greater than or equal to 5.4 Gy in 4 of 19 trials. In no case was the mixed integer solution one fraction size (1.8 Gy) worse than that of simulated annealing. The better solution provided by the mixed integer program allows tumor dose to increase without violating the dose-volume limits of normal tissues. (C) 1996 American Association of Physicists in Medicine.
引用
收藏
页码:957 / 964
页数:8
相关论文
共 50 条
  • [21] APPLICATION OF FAST SIMULATED ANNEALING TO OPTIMIZATION OF CONFORMAL RADIATION TREATMENTS
    MAGERAS, GS
    MOHAN, R
    MEDICAL PHYSICS, 1993, 20 (03) : 639 - 647
  • [22] Solving mixed integer nonlinear chemical engineering problems via simulated annealing approach
    Özçelik, Y
    Özçelik, Z
    CHEMICAL AND BIOCHEMICAL ENGINEERING QUARTERLY, 2004, 18 (04) : 329 - 335
  • [23] New Reflection Generator for Simulated Annealing in Mixed-Integer/Continuous Global Optimization
    H. E. Romeijn
    Z. B. Zabinsky
    D. L. Graesser
    S. Neogi
    Journal of Optimization Theory and Applications, 1999, 101 : 403 - 427
  • [24] New reflection generator for simulated annealing in mixed-integer/continuous global optimization
    Romeijn, HE
    Zabinsky, ZB
    Graesser, DL
    Neogi, S
    JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 1999, 101 (02) : 403 - 427
  • [25] Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems
    Schuster, Richard
    Hanson, Jeffrey O.
    Strimas-Mackey, Matt
    Bennett, Joseph R.
    PEERJ, 2020, 8
  • [26] A Mixed Integer Linear Programming Method for Optimizing Layout of Irrigated Pumping Well in Oasis
    Ma, Teng
    Wang, Jinwen
    Liu, Yi
    Sun, Huaiwei
    Gui, Dongwei
    Xue, Jie
    WATER, 2019, 11 (06)
  • [27] Optimizing wetland restoration and management for avian communities using a mixed integer programming approach
    Stralberg, Diana
    Applegate, David L.
    Phillips, Steven J.
    Herzog, Mark P.
    Nur, Nadav
    Warnock, Nils
    BIOLOGICAL CONSERVATION, 2009, 142 (01) : 94 - 109
  • [28] Combining Mixed Integer Programming and Supervised Learning for Fast Re-planning
    Rachelson, Emmanuel
    Ben Abbes, Ala
    Diemer, Sebastien
    22ND INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2010), PROCEEDINGS, VOL 2, 2010, : 63 - 70
  • [29] A controlled random search technique incorporating the simulated annealing concept for solving integer and mixed integer global optimization problems
    Mohan, C
    Nguyen, HT
    COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 1999, 14 (01) : 103 - 132
  • [30] A Controlled Random Search Technique Incorporating the Simulated Annealing Concept for Solving Integer and Mixed Integer Global Optimization Problems
    C. Mohan
    H.T. Nguyen
    Computational Optimization and Applications, 1999, 14 : 103 - 132