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
  • [41] Optimizing invasive species management: A mixed-integer linear programming approach
    Kibis, Eyyub Y.
    Buyuktahtakin, I. Esra
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2017, 259 (01) : 308 - 321
  • [42] Optimizing Demand-Responsive Paratransit Operations: A Mixed Integer Programming Approach
    Zhang, Xiaojian
    Yang, Yu
    Cochran, Abigail L.
    McDonald, Noreen
    Zhao, Xilei
    2021 55TH ANNUAL CONFERENCE ON INFORMATION SCIENCES AND SYSTEMS (CISS), 2021,
  • [43] APPLICATION OF FAST SIMULATED ANNEALING TO OPTIMIZATION OF CONFORMAL RADIATION TREATMENTS
    MAGERAS, GS
    MOHAN, R
    MEDICAL PHYSICS, 1993, 20 (03) : 639 - 647
  • [44] Combinatorial therapy discovery using mixed integer linear programming
    Pang, Kaifang
    Wan, Ying-Wooi
    Choi, William T.
    Donehower, Lawrence A.
    Sun, Jingchun
    Pant, Dhruv
    Liu, Zhandong
    BIOINFORMATICS, 2014, 30 (10) : 1456 - 1463
  • [45] 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
  • [46] 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
  • [47] 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
  • [48] Scheduling and sequencing jobs on machines by way of integer programming and simulated annealing-based heuristics
    Torres, F
    Troncoso, A
    Blanc, P
    SIMULATION IN INDUSTRY 2001, 2001, : 705 - 708
  • [49] 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
  • [50] Optimizing semiconductor plant inbound logistics by combining dynamic programming and simulated annealing algorithm
    Wu, Chang
    Dong, Ming
    Hou, Wen-Hao
    Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2009, 43 (04): : 572 - 577