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Parameter Identification and Optimization of Chemical Processes

In: DNA Computing Based Genetic Algorithm

Author

Listed:
  • Jili Tao

    (NingboTech University, School of Information Science and Engineering)

  • Ridong Zhang

    (Hangzhou Dianzi University, The Belt and Road Information Research Institute)

  • Yong Zhu

    (NingboTech University, School of Information Science and Engineering)

Abstract

Because of the complex nonlinear characteristics of chemical processes, traditional numerical optimization algorithms generally cannot be used to solve the modeling and optimization problems. In this chapter, the estimation of model parameters for heavy oil thermal cracking is firstly solved by RNA-GA. Then, we use DNA-DHGA to solve the recipe optimization problem of gasoline blending with heavy nonlinear inequality constraints. DNA computing based GAs are efficient in solving the optimization problems in chemical processes.

Suggested Citation

  • Jili Tao & Ridong Zhang & Yong Zhu, 2020. "Parameter Identification and Optimization of Chemical Processes," Springer Books, in: DNA Computing Based Genetic Algorithm, chapter 0, pages 101-118, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-5403-2_5
    DOI: 10.1007/978-981-15-5403-2_5
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