Optimization of dividing wall columns based on online Kriging model and improved particle swarm optimization algorithm

Dividing wall columns (DWCs) can effectively improve the thermodynamic efficiency of traditional distillation columns. However, DWCs have intricate structures and strong internal interactions. Numerous structural and operational variables are interrelated. This work presents an improved cellular par...

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Bibliographic Details
Published in:Computers & chemical engineering Vol. 166; p. 107978
Main Authors: Liang, Mengkun, Song, Jiayin, Zhao, Kefan, Jia, Shengkun, Qian, Xing, Yuan, Xigang
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.10.2022
Subjects:
Dividing wall columns
Heuristic algorithm
Online surrogate model
Optimal design
Particle swarm optimization algorithm
Dividing wall columns
Heuristic algorithm
Online surrogate model
Particle swarm optimization algorithm
Optimal design
ISSN:0098-1354
Online Access:Get full text
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Summary:Dividing wall columns (DWCs) can effectively improve the thermodynamic efficiency of traditional distillation columns. However, DWCs have intricate structures and strong internal interactions. Numerous structural and operational variables are interrelated. This work presents an improved cellular particle swarm optimization based on the online Kriging model (KCPSO) algorithm, and applies it to the optimization of DWC with the objective of minimizing the total annual cost. The algorithm uses the information of particle swarm search to act on the online Kriging model, and reacts on the particle search through the information of the online Kriging model. Calculations demonstrate that the KCPSO algorithm is superior to standard particle swarm optimization (PSO) and cellular PSO (CPSO) algorithms due to its higher quality of iteration. The KCPSO algorithm can effectively overcome the difficulty of early convergence of the CPSO algorithm and the problem that the PSO algorithm is prone to falling into local optimal solutions.
ISSN:0098-1354
DOI:10.1016/j.compchemeng.2022.107978