Volume 31 Issue 2
Mar.  2022
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CUI Jianzhong, YIN Zhixiang, TANG Zhen, YANG Jing. Probe Machine Based Computing Model for Maximum Clique Problem[J]. Chinese Journal of Electronics, 2022, 31(2): 304-312. doi: 10.1049/cje.2020.00.293
Citation: CUI Jianzhong, YIN Zhixiang, TANG Zhen, YANG Jing. Probe Machine Based Computing Model for Maximum Clique Problem[J]. Chinese Journal of Electronics, 2022, 31(2): 304-312. doi: 10.1049/cje.2020.00.293

Probe Machine Based Computing Model for Maximum Clique Problem

doi: 10.1049/cje.2020.00.293
Funds:  This work was supported by the National Natural Science Foundation of China (62072296,61702008) and Natural Science Foundation of Anhui University (KJ2019A0538)
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  • Author Bio:

    was born in 1973, Ph.D. candidate. He received postgraduate degree from Anhui University of Science and Technology. His currently research interests include the combination and optimization, and DNA computing. (Email: 983505198@qq.com)

    (corresponding author), Professor, was born in 1966. He received Ph.D. degree of Huazhong University of Science and Technology. His research interests include the graph theory, combinatorial optimization, DNA computing, and protein structure prediction. He currently serves as the Director of Development and Planning, Anhui University of Science and Technology. (Email: zxyin66@163.com)

    was born in 1994. He is a Ph.D. student. He received his master degree from Anhui University of Science and Technology. His currently research interests include the combination and optimization, and DNA computing. (Email: 983505198@qq.com)

    was born in 1980. She received Ph.D. degree from Anhui University of Science and Technology. Her research interests include the graph, combinatorial optimization, and big data. (Email: jyangh82@163.com)

  • Received Date: 2020-09-11
  • Accepted Date: 2021-09-29
  • Available Online: 2021-11-30
  • Publish Date: 2022-03-05
  • Probe machine (PM) is a recently reported mathematic model with massive parallelism. Herein, we presented searching the maximum clique of an undirected graph with six vertices. We constructed data library containing n sublibraries, each sublibrary corresponded to a vertex in the given graph. Then, probe library according to the induced subgraph was designed in order to search and generate all maximal cliques. Subsequently, we performed probe operation, and all maximal cliques were generated in parallel. The advantages of the proposed model lie in two aspects. On one hand, solution to NP-complete problem is generated in just one step of probe operation rather than found in vast solution space. On the other hand, the proposed model is highly parallel. The work demonstrates that PM is superior to TM in terms of searching capacity when tackling NP-complete problem.
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