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
  • [1] Optimization of beam orientations and beam weights for conformal radiotherapy using mixed integer programming
    Wang, C
    Dai, JR
    Hu, YM
    PHYSICS IN MEDICINE AND BIOLOGY, 2003, 48 (24): : 4065 - 4076
  • [2] Beam orientation optimization for intensity-modulated radiation therapy using mixed integer programming
    Yang, Ruijie
    Dai, Jianrong
    Yang, Yong
    Hu, Yimin
    PHYSICS IN MEDICINE AND BIOLOGY, 2006, 51 (15): : 3653 - 3666
  • [3] Beam orientation optimization for intensity-modulated radiation therapy using mixed integer programming
    Yang, Ruijie
    Dai, Jianrong
    Yang, Yong
    Hu, Yimin
    WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2006, VOL 14, PTS 1-6, 2007, 14 : 1758 - +
  • [4] Hybrid Approaches based on Simulated Annealing and an Exact Algorithm for Mixed Integer Programming Problems
    Tamaki, Keitaro
    Tengan, Takeshi
    Nakamura, Morikazu
    2012 THIRD INTERNATIONAL CONFERENCE ON NETWORKING AND COMPUTING (ICNC 2012), 2012, : 435 - 440
  • [5] Solving discrete lot-sizing and scheduling by simulated annealing and mixed integer programming
    Ceschia, Sara
    Di Gaspero, Luca
    Schaerf, Andrea
    COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 114 : 235 - 243
  • [6] Optimizing simulated annealing schedules with genetic programming
    Bolte, A
    Thonemann, UW
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1996, 92 (02) : 402 - 416
  • [7] Optimizing φ-learning via mixed integer programming
    Liu, Yufeng
    Wu, Yichao
    STATISTICA SINICA, 2006, 16 (02) : 441 - 457
  • [8] Coherent weights for pairwise comparison matrices and a mixed-integer linear programming problem
    Bice Cavallo
    Journal of Global Optimization, 2019, 75 : 143 - 161
  • [9] Coherent weights for pairwise comparison matrices and a mixed-integer linear programming problem
    Cavallo, Bice
    JOURNAL OF GLOBAL OPTIMIZATION, 2019, 75 (01) : 143 - 161
  • [10] A Mixed Linear Integer Programming Formulation and a Simulated Annealing Algorithm for the Mammography Unit Location Problem
    Andrade de Campos, Marcos Vinicius
    Stilpen Moreira de Sa, Manoel Victor
    Rosa, Patrick Moreira
    Vaz Penna, Puca Huachi
    de Souza, Sergio Ricardo
    Freitas Souza, Marcone Jamilson
    PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS (ICEIS), VOL 1, 2020, : 428 - 439