An RWCE Algorithm with Intelligently Adjusted Acceptance Probability of Improper Solutions

doi:10.19596/j.cnki.1001-246x.8214

Abstract

Abstract:

Random walk algorithm with compulsive evolution(RWCE) is an effective method for the optimization of heat exchanger network with advantage of simple evolutionary strategy and less control parameters. The probability of accepting improper solution has important influence on individual jumping out of local optimal solution. We count times of total annual cost decrease in a certain iteration interval in the later stage of optimization, and analyze influence of probability of accepting improper solution in the optimization process. A heat exchange network optimization method is proposed to adjust probability of accepting improper solution with difference between structure of improper solution and original structure. It strengthens evolutionary ability of the algorithm. Effectiveness of the strategy is shown with several examples.

Key words: heat exchanger network, optimization, structure evolution

CLC Number:

TK124

Yiwen JIANG, Guomin CUI, Zihe CHEN, Jiaming YU, Qianqian ZHAO. An RWCE Algorithm with Intelligently Adjusted Acceptance Probability of Improper Solutions[J]. Chinese Journal of Computational Physics, 2021, 38(3): 333-342.

Figures/Tables 14

References 23

1	RUDD D F. The synthesis of system designs: I. Elementary decomposition theory[J]. Aiche Journal, 1968, 14 (2): 343- 349. DOI
2	李志红, 华贲, 尹清华, 等. 人工智能与数学规划的集成用于换热网络最优合成设计的研究[J]. 石油化工, 1998, 9, 36- 44.
3	BJÖRK K M, WESTERLUND T. Global optimization of heat exchanger network synthesis problems with and without the isothermal mixing assumption[J]. Computers & Chemical Engineering, 2002, 26, 1581- 1593.
4	FURMAN K C, SAHINIDIS N V. Approximation algorithms for the minimum number of matches problem in heat exchanger network synthesis[J]. Industrial & Engineering Chemistry Research, 2004, 43 (14): 3554- 3565.
5	CHOI S H, MANOUSIOUTHAKIS V. Global optimization methods for chemical process design: Deterministic and stochastic approaches[J]. Korean Journal of Chemical Engineering, 2002, 19 (2): 227- 232. DOI
6	RAVAGNANI M A S S, SILVA A P, ARROYO P A, et al. Heat exchanger network synthesis and optimisation using genetic algorithm[J]. Applied Thermal Engineering, 2005, 25 (7): 1003- 1017. DOI
7	YERRAMSETTY K M, MURTY C V S. Synthesis of cost-optimal heat exchanger networks using differential evolution[J]. Computers and Chemical Engineering, 2008, 32 (8): 1861- 1876. DOI
8	SILVA A P, RAVAGNANI M A S S, BISCAIA E C, et al. Optimal heat exchanger network synthesis using[J]. Optimization & Engineering, 2010, 11 (3): 459- 470.
9	肖媛, 崔国民, 李帅龙. 一种新的用于换热网络全局优化的强制进化随机游走算法[J]. 化工学报, 2016, 67 (12): 5140- 5147.
10	VITORPAVÃO L, COSTA C B B, SÁRAVAGNANI M A S, et al. Large-scale heat exchanger networks synthesis using simulated annealing and the novel rocket fireworks optimization[J]. AIChE Journal, 2016, 63 (5)
11	LUCAS F S, et al. Synthesis and optimization of work and heat exchanger networks using an MINLP model with a reduced number of decision variables[J]. Applied Energy, 2020, (262)
12	YU S, CUI G, XIAO Y, et al. An improved accepting imperfect network strategy for RWCE algorithm in heat exchanger network synthesis[J]. Chinese Journal of Computational Physics, 2017, 34 (4): 445- 452.
13	孙涛, 崔国民, 肖媛. 采用结构进化增强策略的RWCE算法优化换热网络[J]. 热能动力工程, 2019, 34 (8): 16- 24.
14	KHORASANY R M, FESANGHARY M. A novel approach for synthesis of cost-optimal heat exchanger networks[J]. Computers & Chemical Engineering, 2009, 33 (8): 1363- 1370.
15	HUO Z, ZHAO L, YIN H, et al. Simultaneous synthesis of structural-constrained heat exchanger networks with and without stream splits[J]. Canadian Journal of Chemical Engineering, 2013, 91 (5): 830- 842. DOI
16	ZHANG H, CUI G, XIAO Y, et al. A novel simultaneous optimization model with efficient stream arrangement for heat exchanger network synthesis[J]. Applied Thermal Engineering, 2016, 110, 1659- 1673.
17	VITORPAVÃO L, COSTA C B B, SRAVAGNANI M A S. Heat exchanger network synthesis without stream splits using parallelized and simplified simulated annealing and particle swarm optimization[J]. Chemical Engineering Science, 2017, 158, 96- 107. DOI
18	ZHANG H, CUI G. Optimal heat exchanger network synthesis based on improved cuckoo search via Lévy flights[J]. Chemical Engineering Research and Design, 2018, 134, 62- 79. DOI
19	SORSAK A, KRAVANJA Z. MINLP retrofit of heat exchanger networks comprising different exchanger types[J]. Computers & Chemical Engineering, 2004, 28 (1/2): 235- 251.
20	ESCOBAR M, TRIERWEILER J O. Optimal heat exchanger network synthesis: A case study comparison[J]. Applied Thermal Engineering, 2013, 51 (1/2): 801- 826.
21	BAO Z, CUI G, CAO C, et al. Heat exchanger network optimization based on inner utility placement strategy[J]. Chinese Journal of Computational Physics, 2019, 36 (6): 707- 718.
22	SU G, CUI G, BAO Z, et al. Analysis and treatment on structures with temperature cross in heat exchanger network[J]. Chinese Journal of Computational Physics, 2020, 37 (1): 107- 118.
23	陈子禾, 崔国民, 陈家星, 等. 参数寻优的多个体平行搜索法应用于换热网络全局最优化[J]. 热能动力工程, 2019, 34 (6): 11- 21.

	进口温度T_i/K	出口温度T_o/K	热容流率Fu/(kW·K^-1)	换热系数h/(kW·m^-2·K^-1)
热流体1	658	432	131.51	1.238
热流体2	789	316	1 198.96	0.546
热流体3	405	355	378.52	0.771
热流体4	364	333	589.545	0.859
热流体5	490	316	186.216	1
热流体6	922	316	116	1
冷流体1	303	658	119.1	1.85
冷流体2	372	744	191.05	1.129
冷流体3	710	794	377.91	0.815
冷流体4	351	691.6	160.43	1
冷流体5	490	507	1 297.7	0.443
冷流体6	529	539	2 753	2.085
冷流体7	322	422	197.39	1
冷流体8	332	436.4	123.156	1.063
冷流体9	436	922	95.98	1.81
冷流体10	492	494.3	1 997.5	1.377
热公用工程1	2 073	1 073		1.2
热公用工程2	782	782		1.0
冷公用工程	311	308.5		1.0

	进口温度T_i/K	出口温度T_o/K	热容流率Fu/(kW·K^-1)	换热系数h/(kW·m^-2·K^-1)
热流体1	658	432	131.51	1.238
热流体2	789	316	1 198.96	0.546
热流体3	405	355	378.52	0.771
热流体4	364	333	589.545	0.859
热流体5	490	316	186.216	1
热流体6	922	316	116	1
冷流体1	303	658	119.1	1.85
冷流体2	372	744	191.05	1.129
冷流体3	710	794	377.91	0.815
冷流体4	351	691.6	160.43	1
冷流体5	490	507	1 297.7	0.443
冷流体6	529	539	2 753	2.085
冷流体7	322	422	197.39	1
冷流体8	332	436.4	123.156	1.063
冷流体9	436	922	95.98	1.81
冷流体10	492	494.3	1 997.5	1.377
热公用工程1	2 073	1 073		1.2
热公用工程2	782	782		1.0
冷公用工程	311	308.5		1.0

IT/10⁴	N₁	ΔF₁/($·a^-1)	N₂	ΔF₂/($·a^-1)	N₃	N₄
80~1 000	877	2 583	5 916	357	859	808

IT/10⁴	N₁	ΔF₁/($·a^-1)	N₂	ΔF₂/($·a^-1)	N₃	N₄
80~1 000	877	2 583	5 916	357	859	808

IT/10⁴	δ=0.01	δ=0.001	δ=0.000 1
100~500	4 474	553	42