Individual Reconstruction Optimization Method Applied to Mass Exchanger Networks

doi:10.19596/j.cnki.1001-246x.8682

Abstract

Abstract:

A random walk algorithm compulsive evolution with individual reconstruction strategy is proposed to solve the problem that the optimization of mass exchanger network is easily trapped in local extremum due to the weakening of the ability of structural variation and the loss of population diversity. In the process of receiving differential solutions, real-time monitoring is carried out on individuals, and different reconstruction methods are adopted to stimulate the network structure updating and variation of backward individuals, so as to improve the structural variation ability and population diversity of the algorithm. At the same time, according to the characteristics of the unstructured model with shunt nodes, a new individual network structure after cross reconstruction is repaired. Finally, the R2S2 and R4S2 examples are used to verify the effectiveness of the proposed strategy, and the optimization results are all lower than the results in the current literature, which proves that the proposed strategy can effectively enhance the structural variation ability and global optimization ability of the algorithm.

Key words: mass exchanger network, optimization, local extremum, nodes-based nonstructural model with stream splits, reconstruction

CLC Number:

TK124

Guanglin JIN, Guomin CUI, Yuan XIAO, Hongbin LIU, Yinrui FU, Zhikun ZHANG. Individual Reconstruction Optimization Method Applied to Mass Exchanger Networks[J]. Chinese Journal of Computational Physics, 2024, 41(2): 245-257.

Figures/Tables 17

References 37

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流股	流量/(kg·s^-1)	进口浓度/(kg·kg^-1)	出口浓度/(kg·kg^-1)	m	b	C_j/(＄·kg^-1·a^-1)
R₁	0.9	7.0×10^-2	3.0×10^-4
R₂	0.1	5.1×10^-2	1.0×10^-4
S₁	2.3	6.0×10^-4	3.1×10^-2	1.45	0	117 360
S₂	∞	2.0×10^-4	3.5×10^-3	2.6×10^-1	0	176 040

流股	流量/(kg·s^-1)	进口浓度/(kg·kg^-1)	出口浓度/(kg·kg^-1)	m	b	C_j/(＄·kg^-1·a^-1)
R₁	0.9	7.0×10^-2	3.0×10^-4
R₂	0.1	5.1×10^-2	1.0×10^-4
S₁	2.3	6.0×10^-4	3.1×10^-2	1.45	0	117 360
S₂	∞	2.0×10^-4	3.5×10^-3	2.6×10^-1	0	176 040

	S₁/(kg·s^-1)	S₂/(kg·s^-1)	No of trays	No of units	TAC/(＄·a^-1)
Ref.[30]	2.2	0.23	37	6	469 968
Ref.[9]	2.19	0.32	25	5	431 613
Ref.[11]	2.2	0.33	25	4	429 700
Ref.[31]	2.24	0.37	21	4	422 293
Ref.[32]	2.2	0.3	24	4	420 545
Ref.[29]	2.2	0.37	20	4	412 500
Ref.[16]	2.19	0.36	20	4	411 166
Ref.[14]	2.19	0.38	19	6	410 971
Ref.[33]	2.19	0.37	19	6	410 565
Ref.[17]	2.2	0.32	21	4	409 704
Ref.[18]	2.2	0.3	21	4	407 306
Fig. 12	2.192	0.331	20	5	406 724

	S₁/(kg·s^-1)	S₂/(kg·s^-1)	No of trays	No of units	TAC/(＄·a^-1)
Ref.[30]	2.2	0.23	37	6	469 968
Ref.[9]	2.19	0.32	25	5	431 613
Ref.[11]	2.2	0.33	25	4	429 700
Ref.[31]	2.24	0.37	21	4	422 293
Ref.[32]	2.2	0.3	24	4	420 545
Ref.[29]	2.2	0.37	20	4	412 500
Ref.[16]	2.19	0.36	20	4	411 166
Ref.[14]	2.19	0.38	19	6	410 971
Ref.[33]	2.19	0.37	19	6	410 565
Ref.[17]	2.2	0.32	21	4	409 704
Ref.[18]	2.2	0.3	21	4	407 306
Fig. 12	2.192	0.331	20	5	406 724

流股	流量/(kg·s^-1)	进口浓度/(kg·kg^-1)	出口浓度/(kg·kg^-1)	m	b	C_j/(＄·kg^-1·a^-1)
R₁	3.3	5.0×10^-2	1.5×10^-3
R₂	0.6	7.0×10^-2	3.0×10^-3
R₃	1.4	2.0×10^-2	3.0×10^-2
R₄	0.2	3.0×10^-2	2.0×10^-3
S₁	10	1.3×10^-3	2.5×10^-2	0.71×10^-1	1.0×10^-3	58 680
S₂	10			1.3×10^-1	1.0×10^-3	417 060
Q₁	10	0	5.0×10^-3	1.38		88 020