An Application of the Particle Swarm Optimization on the Gasoline Blending Process

被引：0
|
作者：
Cheng, Hui [1 ]
Zhong, Weimin [1 ]
Qian, Feng [1 ]
机构：
[1] E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China
来源：
APPLIED INFORMATICS AND COMMUNICATION, PT 2 | 2011年 / 225卷
关键词：
Particle Swarm Optimization; Octane Number; Ethyl Model; Gasoline Blending;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an optimization strategy on the basis of the particle swarm optimization (PSO) method is proposed to determine the optimal recipe offline for the gasoline blending process. An octane number model is proposed for optimization. Furthermore, the proposed strategy has been applied onsite at a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the blending process and significantly decrease the quality giveaways and blending cost. The stability of the gasoline production has been improved as well.
引用
收藏
页码：352 / 360
页数：9
相关论文
共 50 条
  • [1] An Application of the Particle Swarm Optimization on the Gasoline Blending Process
    Cheng, Hui
    Zhong, Weimin
    Qian, Feng
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL II, 2010, : 212 - 215
  • [2] Application of Simulated Annealing Particle Swarm Optimization Algorithm in Power Coal Blending Optimization
    Cui Yanbin
    2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 5234 - 5237
  • [3] Blending scheduling based on particle swarm optimization algorithm
    Zhao, Xiaoqiang
    2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5, 2010, : 1192 - 1196
  • [4] Closed-loop scheduling optimization strategy based on particle swarm optimization with niche technology and soft sensor method of attributes-applied to gasoline blending process
    Long, Jian
    Deng, Kai
    He, Renchu
    CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2023, 61 : 43 - 57
  • [5] Particle Swarm Optimization with A Modified Learning Strategy and Blending Crossover
    Panda, Aditya
    Mallipeddi, Rammohan
    Das, Swagatam
    2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017, : 415 - 422
  • [6] Application of an efficient modified particle swarm optimization algorithm for process planning
    Li, Xinyu
    Gao, Liang
    Wen, Xiaoyu
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2013, 67 (5-8): : 1355 - 1369
  • [7] Application of an efficient modified particle swarm optimization algorithm for process planning
    Xinyu Li
    Liang Gao
    Xiaoyu Wen
    The International Journal of Advanced Manufacturing Technology, 2013, 67 : 1355 - 1369
  • [8] Improved particle swarm optimization and its application into optimal preparing process
    Wang Ya-lin
    Wang Ning
    Yang Chun-hua
    Gui Wei-hua
    2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7, 2007, : 3081 - 3085
  • [9] Application on particle swarm optimization algorithms
    Wang, YQ
    Xu, L
    Wang, JH
    Gu, SS
    Yu, XL
    PROGRESS IN INTELLIGENCE COMPUTATION & APPLICATIONS, 2005, : 178 - 183
  • [10] Real Time Optimization of the Gasoline Blending Process with Unscented Kalman Filter
    Cheng, Hui
    Zhong, Weimin
    Qian, Feng
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL II, 2010, : 216 - 219
12345