Highly Parallel Simulated Annealing Applied to the Optimization of Structural Systems

高度并行模拟退火应用于结构系统优化

• 批准号: 12650100
• 负责人: MIKI Mitsunori
• 金额: $ 2.24万
• 依托单位: DOSHISHA UNIVERSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2000
• 资助国家: 日本
• 起止时间: 2000 至 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-12650100/
• 关键词: Optimization; Simulated Annealing; Parallel Processing; PC Clusters; Genetic Algorithms; Structural Systems; Parallel Distributed Model; 並列分散モデル; 並列処理; アプリケーション

Simulated annealing is one of the probabilistic optimization methods for solving complicated optimization problems, and it is started to be used in real world problems recently. However, the method requires many repeated calculations and hence its computational cost becomes very high. Therefore, it is very important and urgent to parallelize the optimization method. Our research is focused on the parallelization of simulated annealing and the development of effective parallel algorithms for parallel simulated annealing. The followings are the conclusions.1) The extension of Temperature Parallel Simulated Annealing to continuous optimization problems is proposed and it provides effective performance.2) The neighborhood range can be automatically adjusted by the proposed method based on the constant probability of acceptance.3) The maximum temperature of the temperature schedule in simulated annealing for continuous optimization problems can be automatically determined by the proposed method where the temperature increases from the lowest temperature instead of cooling.4) A new method for determination of the appropriate neighborhood range based on the parallel annealing with different neighborhood ranges is proposed, and it yields good search performance.

模拟退火算法是解决复杂优化问题的概率优化方法之一，近年来开始应用于真实的世界问题。然而，该方法需要多次重复计算，因此其计算成本变得非常高。因此，对优化方法进行并行化研究是非常重要和迫切的。我们的研究主要集中在模拟退火的并行化和有效的并行模拟退火算法的发展。得出以下结论：1）提出了将温度并行模拟退火算法扩展到连续优化问题，并提供了有效的性能。2）该方法可以根据恒定的接受概率自动调整邻域范围。3）该算法可以自动确定连续优化问题模拟退火算法中的最高温度4）提出了一种基于不同邻域范围并行退火的邻域范围确定方法，该方法具有良好的搜索性能。

项目成果

M. Miki, T. Hiroyasu, K. Ono: "Simulated Annealing with Advanced Adaptive Neighborhood, Computational Intelligence and Applications"Proc. Of the Second International Workshop on Intelligent Systems Design and Applications (ISDA 2002). (2002)

M. Miki、T. Hiroyasu、K. Ono：“具有高级自适应邻域、计算智能和应用的模拟退火”Proc。

三木光範,廣安知之 ら: "連続最適化問題への湿度並列シミュレーテッドアニーリングの応用"情報処理学会論文誌. 41・5. 1607-1616 (2000)

Mitsunori Miki、Tomoyuki Hiroyasu 等人：“湿度并行模拟退火在连续优化问题中的应用”日本信息处理学会会刊 41・5（2000 年）。

M.Miki, T.Hiroyasu, T.Yoshida, T.Fushimi: "Parallel Simulated Annealing with Adaptive Temperature Determined by Genetic Algorithm"Proc.of the 2002 IEEE International Conference on Systems, Man and Cybernetics. (CD-ROM). (2000)

M.Miki、T.Hiroyasu、T.Yoshida、T.Fushimi：“由遗传算法确定的自适应温度的并行模拟退火”Proc.of 2002 IEEE 国际系统、人与控制论会议。

T. Hiroyasu, M. Miki, M. Ogura: "Parallel Simulated Annealing using Genetic Crossover"Proc. Of the IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS 2000). (2000)

T. Hiroyasu、M. Miki、M. Ogura：“使用遗传交叉的并行模拟退火”Proc。

三木光範, 廣安知之, 吉田武史, 実田健: "進化的シミュレーテッドテンパリング"情報処理学会MPSシンポジウム論文集. 351-354 (2001)

Mitsunori Miki、Tomoyuki Hiroyasu、Takeshi Yoshida、Ken Mita：“进化模拟回火”日本 MPS 信息处理学会研讨会论文集 351-354 (2001)。