Constructal optimization design of hybrid microchannel heat sink with single-sided internal fin array and comparative study of genetic algorithms

算法方案		算法策略
		种群个体	最大代数	个体选择策略	个体交叉策略	交叉概率	变异概率	子代种群构成策略
Ⅰ	1	6	10	随机遍历抽样	单点，静态	0.7	0.1	选择全部子代个体
	2	12	10	随机遍历抽样	单点，静态	0.7	0.1
	3	6	20	随机遍历抽样	单点，静态	0.7	0.1
Ⅱ	4	12	10	随机联赛−规模2	单点，静态	0.7	0.1
	5	6	20	随机联赛−规模4，选择100%	单点，静态	0.7	0.1
	6	6	20	随机联赛−规模4，选择70%	单点，静态	0.7	0.1
Ⅲ	7	6	20	随机联赛−规模4，选择100%	单点，静态	0.4	0.1
	8	6	20	随机联赛−规模4，选择100%	单点，静态	0.7	0.3
	9	6	20	随机联赛−规模4，选择100%	单点，动态	0.7，0.4	0.1，0.3
	10	6	20	随机联赛−规模4，选择100%	两点，动态	0.7，0.4	0.1，0.3

Table 2. Optimization results of genetic algorithm schemes No. 1-6

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Table 2. Optimization results of genetic algorithm schemes No. 1-6

算法方案		理论最大个体计算次数	实际个体计算次数	$ {\left({f}_{\nabla T}\right)}_{\mathrm{o}\mathrm{p}\mathrm{t}} $ /(K·m⁻¹)	(h/w)_opt	ε_opt /mm
Ⅰ	1	60	50	4 975.862	5.72	−0.05
	2	120	105	4 979.273	5.52	−0.07
	3	120	104	4 974.012	5.52	−0.12
Ⅱ	4	120	99	4 975.511	5.62	−0.08
	5	120	94	4 978.595	5.36	−0.12
	6	120	97	4 977.800	5.37	−0.08

Table 3. Optimization results of genetic algorithm schemes No. 7-10
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Table 3. Optimization results of genetic algorithm schemes No. 7-10
算法方案 $ {\left({f}_{\nabla T}\right)}_{\mathrm{o}\mathrm{p}\mathrm{t}} $/(K·m⁻¹) (h/w)_opt ε_opt/mm
Ⅲ 7 4 977.900 5.82 −0.07
8 4 975.970 5.72 −0.09
9 4 973.320 5.52 −0.10
10 5 018.800 4.86 −0.18

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Zhuoqun LU, Zhihui XIE, Feng WU, Haili LIU, Rong WANG, Gang NAN. Constructal optimization design of hybrid microchannel heat sink with single-sided internal fin array and comparative study of genetic algorithms[J]. Chinese Journal of Ship Research, 2023, 18(1): 247

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