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多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用

姜培勇 原有进 李朋 殷学军 王志军

姜培勇, 原有进, 李朋, 殷学军, 王志军. 多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用[J]. 原子核物理评论, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415
引用本文: 姜培勇, 原有进, 李朋, 殷学军, 王志军. 多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用[J]. 原子核物理评论, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415
Application of Multi-Objective Particle Swarm Optimization in the Design Optimization of Alternative Phase Focused DTL[J]. Nuclear Physics Review, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415
Citation: Application of Multi-Objective Particle Swarm Optimization in the Design Optimization of Alternative Phase Focused DTL[J]. Nuclear Physics Review, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415

多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用

doi: 10.11804/NuclPhysRev.32.04.415
详细信息
    通讯作者: 姜培勇
  • 中图分类号: O

Application of Multi-Objective Particle Swarm Optimization in the Design Optimization of Alternative Phase Focused DTL

  • 摘要: 现代智能优化算法粒子群算法\,(Particle Swarm Optimization)\,在加速器设计优化上的应用逐渐增多。交变相位聚焦直线加速器\,(Alternative Phase Focused Drift Tube Linac)\,具有节省空间和造价的优点。将交变相位聚焦直线加速器的初步设计方案作为种子,植入粒子群算法中;以加速器的传输效率和束流能量作为目标,得到该方案的Pareto最优解集;在粒子进化过程中,以前沿解集作为粒子的运动方向,以前沿解集的束流径迹作为粒子的参数来源。最终得到了满足能量增益的高传输效率、大接受度的优化方案。

    The Particle Swarm Optimization(PSO), one of the modern intelligent optimization algorithms,is increasingly employed in the design and optimization of accelerators. Alternative Phase Focused Drift Tube Linac(APF DTL) has an advantage in cost-effecient fabrication and reduced construction space. The preliminary design of APF DTL is involved in the optimization as the anchor; by taking the acceleration efficiency and the beam energy as two fitness functions, the Pareto optimal set is obtained; the evolutionary direction is determined by the Pareto optimal set and the particles’ parameters in the optimization are derived from the simulations of the randomly selected Pareto optimal solutions. A final optimized design with extracted energy of 5.35 MeV/u
    and acceleration efficiency greater than 83% is acquired.
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出版历程
  • 收稿日期:  2015-04-19
  • 录用日期:  2015-12-20
  • 刊出日期:  2015-12-20

多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用

doi: 10.11804/NuclPhysRev.32.04.415
    通讯作者: 姜培勇
  • 中图分类号: O

摘要: 现代智能优化算法粒子群算法\,(Particle Swarm Optimization)\,在加速器设计优化上的应用逐渐增多。交变相位聚焦直线加速器\,(Alternative Phase Focused Drift Tube Linac)\,具有节省空间和造价的优点。将交变相位聚焦直线加速器的初步设计方案作为种子,植入粒子群算法中;以加速器的传输效率和束流能量作为目标,得到该方案的Pareto最优解集;在粒子进化过程中,以前沿解集作为粒子的运动方向,以前沿解集的束流径迹作为粒子的参数来源。最终得到了满足能量增益的高传输效率、大接受度的优化方案。

The Particle Swarm Optimization(PSO), one of the modern intelligent optimization algorithms,is increasingly employed in the design and optimization of accelerators. Alternative Phase Focused Drift Tube Linac(APF DTL) has an advantage in cost-effecient fabrication and reduced construction space. The preliminary design of APF DTL is involved in the optimization as the anchor; by taking the acceleration efficiency and the beam energy as two fitness functions, the Pareto optimal set is obtained; the evolutionary direction is determined by the Pareto optimal set and the particles’ parameters in the optimization are derived from the simulations of the randomly selected Pareto optimal solutions. A final optimized design with extracted energy of 5.35 MeV/u
and acceleration efficiency greater than 83% is acquired.

English Abstract

姜培勇, 原有进, 李朋, 殷学军, 王志军. 多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用[J]. 原子核物理评论, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415
引用本文: 姜培勇, 原有进, 李朋, 殷学军, 王志军. 多目标粒子群优化算法在交变相位聚焦直线加速器模拟中的应用[J]. 原子核物理评论, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415
Application of Multi-Objective Particle Swarm Optimization in the Design Optimization of Alternative Phase Focused DTL[J]. Nuclear Physics Review, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415
Citation: Application of Multi-Objective Particle Swarm Optimization in the Design Optimization of Alternative Phase Focused DTL[J]. Nuclear Physics Review, 2015, 32(4): 415-420. doi: 10.11804/NuclPhysRev.32.04.415

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