SCI和EI收录∣中国化工学会会刊

Chinese Journal of Chemical Engineering ›› 2013, Vol. 21 ›› Issue (5): 537-543.DOI: 10.1016/S1004-9541(13)60531-5

• 过程系统工程与过程安全 • 上一篇    下一篇

A Hybrid Algorithm Based on Differential Evolution and Group Search Optimization and Its Application on Ethylene Cracking Furnace

年笑宇, 王振雷, 钱锋   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and Technology, Shanghai 200237, China
  • 收稿日期:2012-07-30 修回日期:2012-10-29 出版日期:2013-05-28 发布日期:2013-05-31
  • 通讯作者: WANG Zhenlei
  • 基金资助:

    Supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (U1162202), the National Natural Science Foundation of China (61174118), the National High Technology Research and Development Program of China (2012AA040307), Shanghai Key Technologies R&D program (12dz1125100) and the Shanghai Leading Academic Discipline Project (B504).

A Hybrid Algorithm Based on Differential Evolution and Group Search Optimization and Its Application on Ethylene Cracking Furnace

NIAN Xiaoyu, WANG Zhenlei, QIAN Feng   

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and Technology, Shanghai 200237, China
  • Received:2012-07-30 Revised:2012-10-29 Online:2013-05-28 Published:2013-05-31
  • Supported by:

    Supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (U1162202), the National Natural Science Foundation of China (61174118), the National High Technology Research and Development Program of China (2012AA040307), Shanghai Key Technologies R&D program (12dz1125100) and the Shanghai Leading Academic Discipline Project (B504).

摘要: To find the optimal operational condition when the properties of feedstock changes in the cracking furnace online, a hybrid algorithm named differential evolution group search optimization (DEGSO) is proposed, which is based on the differential evolution (DE) and the group search optimization (GSO). The DEGSO combines the advantages of the two algorithms: the high computing speed of DE and the good performance of the GSO for preventing the best particle from converging to local optimum. A cooperative method is also proposed for switching between these two algorithms. If the fitness value of one algorithm keeps invariant in several generations and less than the preset threshold, it is considered to fall into the local optimization and the other algorithm is chosen. Experiments on benchmark functions show that the hybrid algorithm outperforms GSO in accuracy, global searching ability and efficiency. The optimization of ethylene and propylene yields is illustrated as a case by DEGSO. After optimization, the yield of ethylene and propylene is increased remarkably, which provides the proper operational condition of the ethylene cracking furnace.

关键词: group search optimization, differential evolution, ethylene and propylene yields, cracking furnace

Abstract: To find the optimal operational condition when the properties of feedstock changes in the cracking furnace online, a hybrid algorithm named differential evolution group search optimization (DEGSO) is proposed, which is based on the differential evolution (DE) and the group search optimization (GSO). The DEGSO combines the advantages of the two algorithms: the high computing speed of DE and the good performance of the GSO for preventing the best particle from converging to local optimum. A cooperative method is also proposed for switching between these two algorithms. If the fitness value of one algorithm keeps invariant in several generations and less than the preset threshold, it is considered to fall into the local optimization and the other algorithm is chosen. Experiments on benchmark functions show that the hybrid algorithm outperforms GSO in accuracy, global searching ability and efficiency. The optimization of ethylene and propylene yields is illustrated as a case by DEGSO. After optimization, the yield of ethylene and propylene is increased remarkably, which provides the proper operational condition of the ethylene cracking furnace.

Key words: group search optimization, differential evolution, ethylene and propylene yields, cracking furnace