caa a22 4500 605468257 CHVBK 20210128100315.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00500-014-1244-6 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1244-6 An improved hybrid immune algorithm for mechanism kinematic chain isomorphism identification in intelligent design [Elektronische Daten] [Ping Yang, Kehan Zeng, Chunquan Li, Jianming Yang, Shuting Wang] In intelligent mechanism design, isomorphism identification of mechanism kinematic chains (IIMKC) is aimed at avoiding repeated mechanism design and is proved to be an NP-complete problem. In this paper, kinematic chains are represented by graphs. An improved hybrid immune algorithm, which integrates the clonal selection immune algorithm with genetic algorithm and the local search algorithm, is proposed to solve IIMKC problem. Moreover, the novel saving and updating operator is proposed to save the best antibodies and maintain a diverse repertoire of antibodies for improving performance of clonal selection. In addition, the pseudo-crossover operator is introduced to enhance the efficiency of genetic algorithm. Simulation results validate the high efficiency and robustness of the hybrid immune algorithm. Springer-Verlag Berlin Heidelberg, 2014 Mechanism kinematic chain isomorphism nationallicence Immune algorithm nationallicence Clonal selection nationallicence Genetic algorithm nationallicence Local search nationallicence Yang Ping School of Mechanical Engineering, Jiangsu University, 212013, Zhenjiang, People's Republic of China aut Zeng Kehan Department of Computer Science, Huizhou University, 516007, Huizhou, People's Republic of China aut Li Chunquan School of Mechanical Engineering, Jiangsu University, 212013, Zhenjiang, People's Republic of China aut Yang Jianming Faculty of Engineering and Applied Science, Memorial University, A1B 3X5, St. John's, NL, Canada aut Wang Shuting School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, People's Republic of China aut Soft Computing Springer Berlin Heidelberg 19/1(2015-01-01), 217-223 1432-7643 19:1<217 2015 19 500 https://doi.org/10.1007/s00500-014-1244-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1244-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yang Ping School of Mechanical Engineering, Jiangsu University, 212013, Zhenjiang, People's Republic of China aut NATIONALLICENCE 700 1- Zeng Kehan Department of Computer Science, Huizhou University, 516007, Huizhou, People's Republic of China aut NATIONALLICENCE 700 1- Li Chunquan School of Mechanical Engineering, Jiangsu University, 212013, Zhenjiang, People's Republic of China aut NATIONALLICENCE 700 1- Yang Jianming Faculty of Engineering and Applied Science, Memorial University, A1B 3X5, St. John's, NL, Canada aut NATIONALLICENCE 700 1- Wang Shuting School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, Hubei, People's Republic of China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/1(2015-01-01), 217-223 1432-7643 19:1<217 2015 19 500