CIESC Journal ›› 2016, Vol. 67 ›› Issue (12): 5140-5147.DOI: 10.11949/j.issn.0438-1157.20160498

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A novel random walk algorithm with compulsive evolution for global optimization of heat exchanger networks

XIAO Yuan, CUI Guomin, LI Shuailong   

  1. Institute of New Energy Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2016-04-18 Revised:2016-07-12 Online:2016-12-05 Published:2016-12-05
  • Supported by:

    supported by the National Natural Science Foundation of China(51176125), the Hujiang Foundation of China(D14001) and the Capacity Building Plan for Some Non-military Universities and Colleges of Shanghai Scientific Committee(16060502600).

一种新的用于换热网络全局优化的强制进化随机游走算法

肖媛, 崔国民, 李帅龙   

  1. 上海理工大学新能源科学与工程研究所, 上海 200093
  • 通讯作者: 崔国民。cgm@usst.edu.cn
  • 基金资助:

    国家自然科学基金项目(51176125);沪江基金研究基地专项(D14001);上海市科委部分地方院校能力建设计划项目(16060502600)。

Abstract:

A novel random walk algorithm with compulsive evolution(RWCE) was proposed on the basis of different heuristic methods for global optimization of heat exchanger networks. In RWCE algorithm, both integer(e.g., number of heat exchanger units) and continuous(e.g., area of heat exchanger) variables were optimized simultaneously by expanding or contracting randomly area of heat exchangers in the direction of targeting cost reduction. Moreover, when individuals walked around local optima, the RWCE algorithm could compulsively accept imperfect networks at certain probability such that it had strong capability of jumping out of the local optima and continuing global optimization. Several case studies indicated that the proposed RWCE algorithm, compared to other heuristic methods, possessed characteristics of simple evolution strategy, strong algorithm suitability and global searchability, which significantly improved optimization performance.

Key words: random walk algorithm with compulsive evolution, heat exchanger network, integer variable, linear variable, optimization

摘要:

应用启发式方法在换热网络全局优化上的优点,提出了一种全新的强制进化随机游走算法(random walk algorithm with compulsive evolution,RWCE),算法以目标函数减小为强制方向,通过各换热单元面积的随机扩大或缩小,同时实现了整型变量(换热单元数)和连续变量(换热单元面积)的同步优化。另外,算法能够以一定的概率选择接受差解,使其具备极强的跳出局部最优解的能力和全局搜索能力。算例验证表明,RWCE算法相比于其他启发式方法具有程序简单、更易实现、算法适应性及全局搜索能力更强的优点,使优化质量得到进一步提升。

关键词: 强制进化随机游走算法, 换热网络, 整型变量, 连续变量, 优化

CLC Number: