Heterogeneous parallel method for mixed integer nonlinear programming

Heterogeneous parallel method for mixed integer nonlinear programming
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混合整数非线性规划的异构并行方法

DOI:
10.1016/j.compchemeng.2013.11.009
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发表时间:
2014-07
期刊:
Computers & Chemical Engineering
影响因子:
--
通讯作者:
Biegler, Lorenz T.
Biegler, Lorenz T.
中科院分区:
其他
文献类型:
--
作者:
Chen, Xi;Shao, Zhijiang;Wan, Wei;Biegler, Lorenz T.

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在异构并行结构下,采用克萨达Grossmann(QG)算法和禁忌搜索(TS)算法同时求解混合整数非线性规划(MINLP)问题。通过在迭代过程中交换三种信息,很好地设计了分别运行两种算法的两个线程之间的通信。首先,TS中的最佳可行解可以成为QG的有效上界。其次,可以在TS提供的节点处生成新的线性化,其可以进一步收紧QG的下限。第三,可以在QG中固定额外的整数变量,从而减小TS的搜索空间。数值结果表明,该方法可以实现良好的性能。进一步的分析表明,异构方法具有潜在的超线性加速比,这可能超过传统的同质并行方法求解MINLP。
In a heterogeneous parallel structure, two types of algorithms, Quesada Grossmann's (QG) algorithm and Tabu search (TS), are used to solve mixed integer nonlinear programming (MINLP) simultaneously. Communication is well designed between two threads running the two algorithms individually by exchanging three kinds of information during iterations. First, the best feasible solution in TS can become a valid upper bound for QG. Second, new linearization which can further tighten the lower bound of QG can be generated at the node provided by the TS. Third, additional integer variables can be fixed in QG, thus reducing the search space of TS. Numerical results show that good performance can be achieved by using the proposed method. Further analysis reveals that the heterogeneous method has the potential for superlinear speedup, which may surpass that of the traditional homogeneous parallel method for solving MINLPs.
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发表时间: 2003
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