Paper Info
Title
Optimization of dividing wall columns based on online Kriging model and improved particle swarm optimization algorithm
Abstract
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.
Year
DOI
Venue
2022
10.1016/j.compchemeng.2022.107978
Computers & Chemical Engineering
Keywords
DocType
Volume
Heuristic algorithm,Online surrogate model,Optimal design,Dividing wall columns,Particle swarm optimization algorithm
Journal
166
ISSN
Citations 
PageRank 
0098-1354
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Mengkun Liang100.34
Jiayin Song200.34
Kefan Zhao300.34
Shengkun Jia400.68
Xing Qian500.34
Yuan Xi-Gang6515.92