CIESC Journal

• 化工学报 • 上一篇    下一篇

大规模过程系统能量优化综合的遗传模拟退火算法

俞红梅,姚平经,袁一,方海鹏,冯恩民   

  1. 大连理工大学化工学院!大连116012,大连理工大学化工学院!大连116012,大连理工大学化工学院!大连116012,大连理工大学数学系!大连116024,大连理工大学数学系!大连116024
  • 出版日期:1998-12-25 发布日期:1998-12-25

IMPROVED GENETIC ALGORITHM/SIMULATED ANNEALING FOR LARGE SYSTEM ENERGY INTEGRATION

Yu Hongmei;Yao Pingjing;Yuan Yi;Fang Haipeng;Feng Enmin(School of Chemical Engineering,Dalian University of Technlogy,Dalian 116012)(Department of Mathematics,Dalian University of Technology,Dalian 116024)   

  • Online:1998-12-25 Published:1998-12-25

摘要: 为求解一般优化算法难以解决的大规模化工系统全过程用能优化综合问题,根据过程用能一致性原则,将其转换为一个大规模虚拟换热网络的求解问题.本文将改进的遗传算法和模拟退火算法有效地结合,增强了遗传算法的搜索能力,预防了传统遗传算法提前收敛的缺陷.数值计算表明,此算法显著优于求解优化问题的遗传算法和模拟退火算法,可处理热、冷流股数超过100的大规模过程系统的用能优化问题,取得了满意的结果.

Abstract: To solve the problem of large system energy integration,which can not be solved by traditional algorithms,a new algorithm named IGA/SA(improved genetic algorithm/simulated algorithm)is Presented in this paper.General genetic algorithm is improved by using OCX and EC factors.Moreover,the improved genetic algorithm is combined with simulated annealing effectively to avoid the common defect of early convergence.IGA/SA was used to solve a 110 stream problem.Good result was achieved to help the total process retrofit.

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