质量交换网络的个体重构优化方法

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

摘要/Abstract

摘要：

针对质量交换网络优化过程中出现结构变异能力减弱和种群多样性丢失, 导致优化易陷入局部最优解的问题, 提出一种带有个体重构策略的强制进化随机游走算法。在接受差解的过程中, 对个体进行实时监测, 采用不同重构方式激励落后个体网络结构更新变异, 从而提升算法的结构变异能力和种群多样性。同时根据有分流节点非结构模型的特点, 对交叉重构后的新个体网络结构进行节点修复处理。最后通过R2S2和R4S2算例验证该策略的有效性, 优化结果均低于当前文献结果, 证明该策略能有效增强算法的结构变异能力和全局寻优能力。

关键词: 质量交换网络, 优化, 局部最优解, 强制进化随机游走算法, 重构

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

中图分类号:

TK124

金广林, 崔国民, 肖媛, 刘洪彬, 付寅瑞, 张志坤. 质量交换网络的个体重构优化方法[J]. 计算物理, 2024, 41(2): 245-257.

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.

图/表 17

图1 质量交换器传质可行性曲线

Fig.1 Mass transfer feasibility curves of mass exchanger

图2 质量交换网络的有分流节点非结构模型

Fig.2 The nodes-based nonstructural model with steam splits of mass exchange network

图3 RWCE算法优化质量交换网络

Fig.3 RWCE algorithm to optimize the mass exchange network

图4 过程最优解与目前优化解的年度总费用曲线(a) 优化过程中；(b) 部分时期过程

Fig.4 Annual total cost curves of the process optimal solution and the current optimized solution

图5 落后个体筛选过程示意图

Fig.5 Schematic diagram of backward individual screening process

图6 清空网络结构的操作流程图

Fig.6 Clear the operation flow chart of the network structure

图7 交叉重构的操作流程图

Fig.7 The operation flow chart of cross reconstruction

图8 交叉重构操作示意图

Fig.8 Schematic diagram of the cross reconstruction operation

图9 节点被重复连接的修复示意图

Fig.9 Repair diagram of the nodes being repeatedly connected

图10 个体重构策略融入RWCE算法(IR-RWCE)的流程

Fig.10 The process of integrating individual reconstruction strategy into RWCE algorithm (IR-RWCE)

图11 不同λ的年度总费用下降曲线

Fig.11 Annual total cost decline curve at different λ

表1 R2S2算例的流股数据

Table 1 The floating stock data of R2S2 Case

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

图12 R2S2算例的网络结构 (a)基础算法；(b)改进后算法

Fig.12 Network structure of R2S2 Case (a) RWCE; (b) IR-RWCE

表2 R2S2算例的结果对比

Table 2 Comparison of results of R2S2 Case

	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

表3 R4S2算例的流股数据

Table 3 The streams data of R4S2 Case

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

图13 R4S2算例的网络结构 (a) 基础算法；(b) 改进后算法

Fig.13 Network structure of Case R4S2 (a) RWCE; (b) IR-RWCE

表4 R4S2算例的结果对比

Table 4 Comparison of results in R4S2 Case

	S₁/(kg·s^-1)	S₂/(kg·s^-1)	Q₁/(kg·s^-1)	No. of trays	Total packed height/m	TAC/(＄·a^-1)
Ref.[34]	9.33	282	3.2	20	8.71	957 000
Ref.[35]	9.6	0.319	0.40	20	3.858	706 000
Ref.[9]	9.602	0.349	0.422	17	3.752	694 000
Ref.[36]	9.576	0.442	0.391	16	0.476 84	689 300
Ref.[37]	9.572 17	0.346 33	0.484 6	16	2.768	688 932
Fig. 13	9.576	0.331	0.457 6	15	3.889 2	686 954

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