SCI和EI收录∣中国化工学会会刊

›› 2017, Vol. 25 ›› Issue (8): 983-991.DOI: 10.1016/j.cjche.2017.03.022

• Article •    下一篇

Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm

Lili Tao1, Bin Xu2, Zhihua Hu1, Weimin Zhong3   

  1. 1 College of Engineering, Shanghai Polytechnic University, Shanghai 201209, China;
    2 School of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China;
    3 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:2016-09-16 修回日期:2016-10-22 出版日期:2017-08-28 发布日期:2017-09-11
  • 通讯作者: Lili Tao, Weimin Zhong
  • 基金资助:
    Supported by the Shanghai Second Polytechnic University Key Discipline Construction-Control Theory&Control Engineering (No.XXKPY1609),the National Natural Science Foundation of China (61422303),Shanghai Talent Development Funding (H200-2R-15111),and 2017 Shanghai Second Polytechnic University Cultivation Research Program of Young Teachers (02).

Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm

Lili Tao1, Bin Xu2, Zhihua Hu1, Weimin Zhong3   

  1. 1 College of Engineering, Shanghai Polytechnic University, Shanghai 201209, China;
    2 School of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China;
    3 Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2016-09-16 Revised:2016-10-22 Online:2017-08-28 Published:2017-09-11
  • Supported by:
    Supported by the Shanghai Second Polytechnic University Key Discipline Construction-Control Theory&Control Engineering (No.XXKPY1609),the National Natural Science Foundation of China (61422303),Shanghai Talent Development Funding (H200-2R-15111),and 2017 Shanghai Second Polytechnic University Cultivation Research Program of Young Teachers (02).

摘要: The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemical process in industry [1]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simultaneously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization problems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm (SADE) to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm (ISADE). Optimization results indicate that application of ISADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.

关键词: p-Xylene oxidation, Operation condition optimization, Multi-objective optimization, Self-adaptive differential evolution

Abstract: The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemical process in industry [1]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simultaneously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization problems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm (SADE) to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm (ISADE). Optimization results indicate that application of ISADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.

Key words: p-Xylene oxidation, Operation condition optimization, Multi-objective optimization, Self-adaptive differential evolution