Heterogeneous parallel method for mixed integer nonlinear programming

作     者：Zhou, Kai Chen, Xi Shao, Zhijiang Wan, Wei Biegler, Lorenz T. 

作者机构：Zhejiang Univ Dept Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310003 Zhejiang Peoples R China Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA 

出 版 物：《COMPUTERS & CHEMICAL ENGINEERING》 (计算机与化工)

年 卷 期：2014年第66卷

页      面：290-300页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China  NSFC  (21206149  61074148) 

主　　题：Mixed integer nonlinear programming Parallel computing Heterogeneous method 

摘      要：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. (c) 2013 Elsevier Ltd. All rights reserved.