采用三层保护策略的强制进化随机游走算法同步综合换热网络
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  • 英文篇名:Simultaneous Synthesis of Heat Exchanger Network by Random Walk Algorithm with Compulsive Evolution Based on Trilevel Protection Strategy
  • 作者:李剑 ; 崔国民 ; 陈家星 ; 肖媛
  • 英文作者:LI Jian;CUI Guomin;CHEN Jiaxing;XIAO Yuan;Institute of New Energy Science and Engineering, University of Shanghai for Science and Technology;
  • 关键词:换热网络 ; 强制进化随机游走算法 ; 接受差解 ; 全局搜索 ; 局部搜索
  • 英文关键词:heat exchanger network;;random walk algorithm with compulsive evolution;;accept imperfect solution;;global search;;local search
  • 中文刊名:JSWL
  • 英文刊名:Chinese Journal of Computational Physics
  • 机构:上海理工大学新能源科学与工程研究所;
  • 出版日期:2018-03-29 11:46
  • 出版单位:计算物理
  • 年:2019
  • 期:v.36;No.185
  • 基金:国家自然科学基金(51176125);; 上海市科委部分地方院校能力建设计划(16060502600)资助项目
  • 语种:中文;
  • 页:JSWL201901008
  • 页数:11
  • CN:01
  • ISSN:11-2011/O4
  • 分类号:73-83
摘要
强制进化随机游走算法(RWCE)同步综合换热网络时,存在个体最优解的进化路径被接受差解打乱而不接受差解又很难跳出局部最优的问题.提出一种采用三层保护策略的RWCE算法,将种群中个体分为三层,底层采用基本RWCE进行优化,以保护个体的全局搜索能力;中层读取底层各个体的历史最优解,并采用带微调功能的RWCE进行优化,以保护各个体最优解的进化路径不被打乱;顶层所有个体以中层最优个体的解为初始点,采用带自动精细搜索功能的RWCE进行优化,以保证最优个体得到充分的搜索;最后将顶层搜索到的结果传递给底层对应个体.实例表明,算法在允许接受差解的同时保护了个体最优解的进化路径,并实现了全局搜索能力与局部搜索能力的兼顾.
        To avoid the problem of being disturbed by stochastic acceptance of imperfect solution for evolution process of individual optimal solution existing in optimization of heat exchanger network by random walk algorithm with compulsive evolution, an improved RWCE based on trilevel protection strategy is proposed. Individuals in population are divided into three levels. The lower-level is optimized by basic RWCE to protect global search ability of individuals. The middle-level reads historical optimal solution of the lower-level's individuals, and optimized by RWCE with fine tuning to protect evolution process of each individual′s optimal solution from disruption. All individuals in the upper-level are initialized by solution of the best individuals in the middle-level, and optimized by RWCE with automatic fine search to ensure that the best individuals are fully searched. Finally, result of the upper-level is passed to corresponding individual at the lower-level. Two cases are optimized by using the algorithm,and results are better than those in literature. Evolution process of individual optimal solution is protected while accepting imperfect solution, therefore, both global search ability and local search ability are realized.
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