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Applied Artificial Intelligence
An International Journal
Volume 35, 2021 - Issue 2
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Research Article

A Hybrid Greedy Sine Cosine Algorithm with Differential Evolution for Global Optimization and Cylindricity Error Evaluation

Qijun Lia School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, China;b School of Electromechanics and Automobile Engineering, Tianshui Nomal University, Tianshui, ChinaORCID Iconhttps://orcid.org/0000-0001-7836-5462View further author information
ORCID Icon,
Huifeng Ninga School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, ChinaView further author information
,
Jun Gonga School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, ChinaCorrespondence[email protected]
View further author information
,
Xiao Lia School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, ChinaView further author information
&
Baolin Daia School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, ChinaORCID Iconhttps://orcid.org/0000-0003-4332-135XView further author information
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Pages 171-191 | Received 06 Sep 2020, Accepted 06 Nov 2020, Published online: 15 Dec 2020

Figures & data

Table 1. The historical memory

Table 2. The parameters of algorithms and their values

Table 3. Wilcoxon signed rank test between HGSCADE and other algorithms for the CEC2014 functions with D = 30 at a 5% level of significance

Table 4. The cylindricity error evaluation results of different algorithms

Figure 1. The convergence curves of all algorithms for certain CEC2014 functions (H3, H13, H20, and H30) with D = 30

Figure 1. The convergence curves of all algorithms for certain CEC2014 functions (H3, H13, H20, and H30) with D = 30

Figure 2. The convergence curves of all algorithms for certain CEC2014 functions (H3, H13, H20, and H30) with D = 50

Figure 2. The convergence curves of all algorithms for certain CEC2014 functions (H3, H13, H20, and H30) with D = 50

Figure 3. Schematic of cylindricity error

Figure 3. Schematic of cylindricity error

Table 5. Mean and standard deviation of 51 independent runs for all algorithms on the CEC2014 functions with D = 30

Figure 4. The convergence curves of all algorithms for cylindricity error evaluation

Figure 4. The convergence curves of all algorithms for cylindricity error evaluation

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