[1] 李伯虎, 张霖, 王时, 等. 云制造——面向服务的网络化制造新模式[J]. 计算机集成制造系统, 2010, 16(1): 1-7, 16 LI Bohu, ZHANG Ling, WANG Shi, et al. Cloud manufacturing: a new service-oriented networked manufacturing model[J]. Computer Integrated Manufacturing Systems, 2010, 16(1): 1-7, 16 [2] 苑彬彬. 现代制造企业分包运营管理的探析[J]. 中国外资, 2020(20): 42-44 YUAN Binbin. Analysis of subcontract operation management in modern manufacturing enterprises[J]. Foreign Investmentin China, 2020(20): 42-44 [3] WANG S, LU Y, CHU F, et al. Scheduling with divisible jobs and subcontracting option[J]. Computers and Operations Research, 2022, 145(1): 105850 [4] 金鸿, 姚锡凡, 杨洲, 等. 基于教—学算法的制造云服务组合优化[J]. 计算机集成制造系统, 2018, 24(1): 43-52 JIN Hong, YAO Xifan, YANG Zhou, et al. Manufacturing cloud service composition of teaching-learning based optimization[J]. Computer Integrated Manufacturing Systems, 2018, 24(1): 43-52 [5] 李贻婷. 基于混合算法的云制造资源配置研究[J]. 自动化与信息工程, 2022, 43(2): 41-44, 48 LI Yiting. Research on cloud manufacturing resource allocation based on hybrid algorithm[J]. Automation & Information Engineering, 2022, 43(2): 41-44, 48 [6] 吴书强, 栾飞. 基于改进型鲸鱼算法的云制造资源配置研究[J]. 制造业自动化, 2019, 41(12): 95-98, 124 WU Shuqiang, LUAN Fei. Optimal allocation method for cloud manufacturing resource base on improved whale optimization algorithm[J]. Manufacturing Automation, 2019, 41(12): 95-98, 124 [7] 李雪, 李芳. 云环境下大规模定制中资源配置研究[J]. 工业工程, 2021, 24(1): 147-154 LI Xue, LI Fang. A research on resource allocation in mass customization under cloud environment[J]. Industrial Engineering Journal, 2021, 24(1): 147-154 [8] 张晖明, 邓霆. 规模经济的理论思考[J]. 复旦学报 (社会科学版), 2002(1): 25-29 ZHANG Huiming, DENG Ting. Theoretical reflections on scale economy[J]. Fudan University Journal (Social Sciences Edition), 2002(1): 25-29 [9] 王婷, 卫少鹏, 廖斌, 等. 国内外智能调度研究现状、热点与发展趋势——基于CiteSpace的可视化对比研究[J]. 工业工程, 2020, 23(2): 105-115 WANG Ting, WEI Shaopeng, LIAO Bin, et al. The status quo, hotspots and development trends of intelligent scheduling at home and abroad—visualization contrast research based on citespace[J]. Industrial Engineering Journal, 2020, 23(2): 105-115 [10] KAUR S, AWASTHI K L, SANGAL A L, et al. Tunicate swarm algorithm: a new bio-inspired based metaheuristic paradigm for global optimization[J]. Engineering Applications of Artificial Intelligence, 2020, 90(C): 103541 [11] SHARMA A, DASGOTRA A, TIWARI K S, et al. Parameter extraction of photovoltaic module using tunicate swarm algorithm[J]. Electronics, 2021, 10(8): 878 [12] RIZK-ALLAH M R, SALEH O, HAGAG A E, et al. Enhanced tunicate swarm algorithm for solving large-scale nonlinear optimization problems[J]. International Journal of Computational Intelligence Systems, 2021, 14(1): 189 [13] 屈迟文, 彭小宁. 信息共享的记忆被囊群算法[J]. 模式识别与人工智能, 2021, 34(7): 605-618 QU Chiwen, PENG Xiaoning. Memory tunicate swarm algorithm with information sharing[J]. Pattern Recognition and Artificial Intelligence, 2021, 34(7): 605-618 [14] 史鸿锋, 李永林. 精英反向黄金正弦被囊群优化算法[J]. 智能计算机与应用, 2021, 11(11): 189-193, 197 SHI Hongfeng, LI Yonglin. Elite Opposition-based golden-sine tunicate swarm algorithm[J]. Intelligent Computer and Applications, 2021, 11(11): 189-193, 197 [15] 王海宁, 王正莹, 慕子煜, 等. 基于层次分析法的EPC总承包物资采购评标权重选取[J]. 电力勘测设计, 2022(6): 1-5 WANG Haining, WANG Zhengying, MU Ziyu, et al. Selection of evaluation weight of EPC material procurement based on AHP[J]. Electric Power Survey & Design, 2022(6): 1-5 [16] EBERHART R, KENNEDY J. A new optimizer using particle swarm theory[C]//MHS’95. Proceedings of Sixth International Symposium On Micro Machine and Human Science. Nagoya, Japan: IEEE Service Center, 1995: 39-43. [17] ARORA S, SINGH S. Butterfly optimization algorithm: a novel approach for global optimization[J]. Soft Computing, 2019, 23(3): 715-734 [18] STORN R, PRICE K. Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11(4): 341-359 [19] RAJABIOUN R. Cuckoo optimization algorithm[J]. Applied Soft Computing Journal, 2011, 11(8): 5508-5518
|