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A restructured artificial bee colony optimizer combining life-cycle, local search and crossover operations for droplet property prediction in printable electronics fabrication
Jing, Shikai; Ma LB(马连博); Hu KY(胡琨元); Zhu YL(朱云龙); Chen HN(陈瀚宁)
Department信息服务与智能控制技术研究室
Source PublicationJournal of Intelligent Manufacturing
ISSN0956-5515
2018
Volume29Issue:1Pages:109–134
Indexed BySCI ; EI
EI Accession number20152300902142
WOS IDWOS:000419167400007
Contribution Rank2
Funding OrganizationNational Natural Science Foundation of China (Nos. 61174164, 61203161, and 51205389) and Liaoning Provincial Natural Science Foundation of China (2014010094-301)
KeywordArtificial Bee Colony Algorithm Life-cycle • Local Search Crossover Printable Electronics Droplet Property Prediction
AbstractFor printable electronics fabrication, a major challenge is the print resolution and accuracy delivered by a drop-on-demand piezoelectric inkjet printhead. In order to meet the challenging requirements of printable electronics fabrication, this paper proposes a novel restructured artificial bee colony optimizer called HABC for optimal prediction of the droplet volume and velocity. The main idea of HABC is to develop an adaptive and cooperative scheme by combining life-cycle, Powell’s search and crossover-based social learning strategies for complex optimizations. HABC is a more biologically-realistic model that the reproduce and die dynamically throughout the foraging process and the population size varies as the algorithm runs. With the crossover operator, the information exchange ability of the bees can be enhanced in the early exploration phase while the Powell’s search enables the bees deeply exploit around the promising area, which provides an appropriate balance between exploration and exploitation. The proposed algorithm is benchmarked against other four state-of-the-art bio-inspired algorithms using both classical and CEC2005 test function suites. Then HABC is applied to predict the printing quality using nano-silver ink. Statistical analysis of all these tests highlights the significant performance improvement due to the beneficial combination and shows that the proposed HABC outperforms the reference algorithms.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Manufacturing
WOS KeywordNUMERICAL FUNCTION OPTIMIZATION ; GLOBAL OPTIMIZATION ; PARTICLE SWARM ; ALGORITHM ; EVOLUTION
WOS Research AreaComputer Science ; Engineering
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/16151
Collection信息服务与智能控制技术研究室
Corresponding AuthorChen HN(陈瀚宁)
Affiliation1.School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 110081, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.School of Computer Science and Software, Tianjin Polytechnic University, Tianjin, 300387, China
Recommended Citation
GB/T 7714
Jing, Shikai,Ma LB,Hu KY,et al. A restructured artificial bee colony optimizer combining life-cycle, local search and crossover operations for droplet property prediction in printable electronics fabrication[J]. Journal of Intelligent Manufacturing,2018,29(1):109–134.
APA Jing, Shikai,Ma LB,Hu KY,Zhu YL,&Chen HN.(2018).A restructured artificial bee colony optimizer combining life-cycle, local search and crossover operations for droplet property prediction in printable electronics fabrication.Journal of Intelligent Manufacturing,29(1),109–134.
MLA Jing, Shikai,et al."A restructured artificial bee colony optimizer combining life-cycle, local search and crossover operations for droplet property prediction in printable electronics fabrication".Journal of Intelligent Manufacturing 29.1(2018):109–134.
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