Parallel Solution of Large-Scale Dynamic Optimization Problems

被引:0
|
作者
Laird, Carl D. [1 ]
Wong, Angelica V. [1 ]
Akesson, Johan [2 ]
机构
[1] Texas A&M Univ, Artie McFerrin Dept Chem Engn, College Stn, TX 77843 USA
[2] Lund Univ, Dept Automat Control, S-22100 Lund, Sweden
来源
21ST EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING | 2011年 / 29卷
基金
美国国家科学基金会;
关键词
dynamic optimization; parallel computing; collocation;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents a decomposition strategy applicable to DAE constrained optimization problems. A common solution method for such problems is to apply a direct transcription method and to solve the resulting non-linear program using an interior point algorithm, where the time to solve the linearized KKT system at each iteration is dominating the total solution time. In the proposed method, the structure of the KKT system resulting from a direct collocation scheme for approximating the DAE constraint is exploited in order to distribute the required linear algebra operations on multiple processors. A prototype implementation applied to benchmark models shows promising results.
引用
收藏
页码:813 / 817
页数:5
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