Parallel computing based parameter auto-tuning algorithm for optimization solvers

被引：0
作者：
机构：
[1] State Key Laboratory of Industrial Control Technology, Institute of Industrial Control, Zhejiang University, Hangzhou 310027, Zhejiang
[2] College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang
来源：
Shao, Z. (zjshao@iipc.zju.edu.cn) | 2013年 / Materials China卷 / 64期
关键词：
Numerical simulation; Optimization; Parallel computing; Parameter auto-tuning; Process systems;
D O I：
10.3969/j.issn.0438-1157.2013.12.027
中图分类号：
学科分类号：
摘要：
Parameter setting plays an important role in the performance of optimization solver. Hence, the potential solving performance can be full employed by tuning the parameters. The increase of complexity and scale of process model has a great influence on the efficiency of parameter auto-tuning algorithm. In this paper, according to the independence of the parameter setting selection and evaluation of the random sampling based parameter auto-tuning algorithm, the efficiency is improved by utilizing parellel technology. The numerical experiment shows that the parallel computing based parameter auto-tuning algorithm has an enhanced tuning efficiency and it is suitable to online operation optimization for operation run of production process with sufficient hardware support. © All Rights Reserved.
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页码：4446 / 4453
页数：7
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