Parallel computing based parameter auto-tuning algorithm for optimization solvers

doi:10.3969/j.issn.0438-1157.2013.12.027

CIESC Journal ›› 2013, Vol. 64 ›› Issue (12): 4446-4453.DOI: 10.3969/j.issn.0438-1157.2013.12.027

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Parallel computing based parameter auto-tuning algorithm for optimization solvers

CHEN Weifeng^1,2, CHEN Jie², SHAO Zhijiang¹

1. State Key Laboratory of Industrial Control Technology, Institute of Industrial Control, Zhejiang University, Hangzhou 310027, Zhejiang, China;
2. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China

Received:2013-08-13 Revised:2013-08-22 Online:2013-12-05 Published:2013-12-05
Supported by:
supported by the National Basic Research Program of China (2009CB320603) and the State Key Laboratory of Industrial Control Technology Program (ICT1227).

基于并行计算的优化方法参数自动整定算法

陈伟锋^1,2, 陈杰², 邵之江¹

1. 浙江大学工业控制技术国家重点实验室, 工业控制研究所, 浙江杭州 310027;
2. 浙江工业大学信息工程学院, 浙江杭州 310023

通讯作者: 邵之江
作者简介:陈伟锋（1984- ），男，博士，讲师。
基金资助:
国家重点基础研究发展计划项目（2009CB320603）；工业技术国家重点实验室开放基金（ICT1227）。

Abstract

Abstract: 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.

Key words: optimization, process systems, numerical simulation, parallel computing, parameter auto-tuning

摘要： 优化求解器的参数设置对优化求解器的性能有着至关重要的影响，可以通过参数整定来充分发挥优化求解器潜在的求解性能。过程模型复杂程度的提高和规模的增大，给参数自动整定算法的效率带来极大的影响。根据基于随机采样的参数自动整定算法对每一组参数设置的选择和评估是相互独立的特点，采用并行化方法对其进行了改进。数值实验表明基于并行计算的参数自动整定能够提高整定效率，并且在足够的硬件条件支持下适合应用于面向生产过程的操作运行的在线操作优化。

关键词: 优化, 过程系统, 数值模拟, 并行计算, 参数自动整定

CLC Number:

TQ021.8

CHEN Weifeng, CHEN Jie, SHAO Zhijiang. Parallel computing based parameter auto-tuning algorithm for optimization solvers[J]. CIESC Journal, 2013, 64(12): 4446-4453.

陈伟锋, 陈杰, 邵之江. 基于并行计算的优化方法参数自动整定算法[J]. 化工学报, 2013, 64(12): 4446-4453.

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Parallel computing based parameter auto-tuning algorithm for optimization solvers

基于并行计算的优化方法参数自动整定算法

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