李俊青

一、IEEE Transactions长文

[22] Xiaolong Chen, Li, Junqing(通讯作者), Zunxun Wang, Qingda Chen, Kaizhou Gao, Quanke Pan. Optimizing Dynamic Flexible Job Shop Scheduling Using an Evolutionary Multi-Task Optimization Framework and Genetic Programming. IEEE Transactions on Evolutionary Computation , 2025.2.

[21] Li, Junqing; Li, Jiake; Gao Kaizhou; Duan Peiyong. A hybrid graph-based imitation learning method for a realistic distributed hybrid flow shop with family setup time. IEEE Transactions on Systems, Man and Cybernetics: Systems , vol. 54, no. 12, pp. 7291-7304, 2024.

[20] Junqing Li, Yuyan Han, Kaizhou Gao, Xiumei Xiao, Peiyong Duan. Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation. IEEE Transactions on Automation Science and Engineering , , 2024, 21(3): 4686-4702. TASE-2024

[19] Du, Yu; Li, Junqing(通讯作者); Li, Chengdong; Duan, Peiyong. A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times, IEEE Transactions on Neural Networks and Learning Systems, 35 (4): 5695-5709, 2024.

[18] Du Yu, Li Junqing(李俊青，通讯作者), Chen Xiaolong, Duan Peiyong, Pan Quanke. A knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023, 7(4): 1036-1050.

[17] Mou, J., Gao, K., Duan, P., Li Junqing(李俊青，通讯作者)., Garg, A., & Sharma, R. A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(12): 15527-15539.

[16] Li Junqing, Chen Xiaolong, Duan Peiyong, Mou jianhui, KMOEA: A knowledge-based multi-objective algorithm for distributed hybrid flow shop in a prefabricated system.. IEEE Transactions on Industrial Informatics , 2022, 18(8): 5318-5329..

[15] Li, Junqing; Du, Yu; Gao, Kai-zhou; Duan, Pei-yong; Gong, Dun-Wei; Pan, Quanke; Suganthan, P N. A hybrid iterated greedy algorithm for a crane transportation flexible job shop problem. IEEE Transactions on Automation Science and Engineering , 2022, 19(3): 2153-2170.

[14] Li Junqing, Liu Zhengmin, Li Chengdong, Zheng Zhixin. Improved artificial immune system algorithm for Type-2 fuzzy flexible job shop scheduling problem. IEEE Transactions on Fuzzy Systems , 2021, 29(11):3234-3248. 2020-TFS.pdf

[13] Li, Jun-qing (李俊青), Song Meixian., Wang Ling., Duan Peiyong., Han Yuyan., Sang Hongyan, Pan Quanke. Hybrid artificial bee colony algorithm for a parallel batching distributed flow shop problem with deteriorating jobs, IEEE Transactions on Cybernetics, 2020, 50(6): 2425-2439. 2020-TCYB.pdf

[12] Li JQ(李俊青), Pan QK, Duan PY(段培永，通讯作者), Sang HY. Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm. IEEE/CAA Journal of Automatica Sinica, 2019, 6(5): 1240-1250.

[11] Li, Jun-qing (李俊青), Pan Quan-ke, Duan Pei-yong. An Improved Artificial Bee Colony Algorithm for Solving Hybrid Flexible Flowshop with Dynamic Operation Skipping, IEEE Transactions on Cybernetics, 46(6), 1311-1324 . 2016-TCYB.pdf

[10] Li, Jun-qing (李俊青), Pan Quan-ke, Mao Kun. A Hybrid Fruit Fly Optimization Algorithm for the Realistic Hybrid Flowshop Rescheduling Problem in Steelmaking Systems. IEEE Transactions on Automation Science and Engineering , 13(2): 932-949, 2016. 2016-TASE.pdf

[9] Sun, J., Miao, Z., Gong, D., Zeng, X. J., Li Junqing(李俊青), & Wang, G. (2020). Interval Multiobjective Optimization With Memetic Algorithms. IEEE transactions on cybernetics, 2020, doi: 10.1109/TCYB.2019.2908485.

[8] Qingda Chen, Quanke Pan, Biao Zhang, Jinliang Ding, Li Junqing(李俊青). Effective Hot Rolling Batch Scheduling Algorithms in Compact Strip Productio. IEEE Transactions on Automation Science and Engineering, 16 (4) (2019) 1933-1951.

[7] Pan Quanke, Ling Wang, Hong-yan Sang, Li Junqing(李俊青), and Min Liu. A High Performing Memetic Algorithm for the Flowshop Scheduling Problem With Blocking. IEEE Transactions on Automation Science And Engineering, 10(3), 2013: 741-756.

[6] H. Li, K. Gao, P.-Y. Duan, Li Junqing(李俊青) and L. Zhang, "An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems," IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, doi: 10.1109/TSMC.2022.3219380.

[5] Niu, B., Liu, J., Duan, P., Li Junqing(李俊青), & Yang, D. (2019). Reduced-order observer-based adaptive fuzzy tracking control scheme of stochastic switched nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(7), 4566-4578.

[4] Niu, B. Liu, JD. Duan, PY. Li Junqing(李俊青). Yang, D. Multialgorithm Fusion Image Processing for High Speed Railway Dropper Failure-Defect Detection. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51(7): 4566-4578.

[3] Niu, B., Li, H., Zhang, Z., Li Junqing(李俊青), Hayat, T., & Alsaadi, F. E. (2018). Adaptive neural-network-based dynamic surface control for stochastic interconnected nonlinear nonstrict-feedback systems with dead zone. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(7), 1386-1398.

[2] Niu, B, Yanjun Liu, Wanlu Zhou, Haitao Li, Peiyong Duan, Li Junqing(李俊青). Multiple Lyapunov Functions for Adaptive Neural Tracking Control of Switched Nonlinear Nonlower-Triangular Systems, IEEE transactions on cybernetics, 2019, doi: 10.1109/TCYB.2019.2906372

[1] Niu, B., Duan, P.,Li Junqing(李俊青), & Li, X. (2020). Adaptive Neural Tracking Control Scheme of Switched Stochastic Nonlinear Pure-Feedback Nonlower Triangular Systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, doi: 10.1109/TSMC.2019.2894745.

二、代表性论文（一作）

[32] Li, Junqing; Li, Jiake; Gao Kaizhou; Duan Peiyong. A hybrid graph-based imitation learning method for a realistic distributed hybrid flow shop with family setup time. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2024, 54(12): 7291-7304.

[31] Li, Junqing(通讯作者), Jiake Li; Kaizhou Gao; Ying Xu. A double-Q network collaborative multi-objective optimization algorithm for precast scheduling with curing constraints. Swarm and Evolutionary Computation, 89, 101619, 2024.

[30] Li, Junqing(通讯作者), Jiake Li; Kaizhou Gao; Peiyong Duan. Two-level balancing multi-objective algorithm for trapezoidal type-2 fuzzy flexible job shop problems. Information Sciences, 2024, 678 (9): 121011.

[29] Li, Junqing(通讯作者), Jiake Li; Kaizhou Gao; Ying Xu. A double-Q network collaborative multi-objective optimization algorithm for precast scheduling with curing constraints. Swarm and Evolutionary Computation, 101619, 2024.

[28] Junqing Li, Yuyan Han, Kaizhou Gao, Xiumei Xiao, Peiyong Duan. Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation. IEEE Transactions on Automation Science and Engineering , , 2024, 21(3): 4686-4702. TASE-2024

[27] Li Junqing, Chen Xiaolong, Duan Peiyong, Mou jianhui, KMOEA: A knowledge-based multi-objective algorithm for distributed hybrid flow shop in a prefabricated system. IEEE Transactions on Industrial Informatics , 2021, 10.1109/TII.2021.3128405.

[26] Li, Junqing; Du, Yu; Gao, Kai-zhou; Duan, Pei-yong; Gong, Dun-Wei; Pan, Quanke; Suganthan, P N. A hybrid iterated greedy algorithm for a crane transportation flexible job shop problem. IEEE Transactions on Automation Science and Engineering , 2021, doi: 10.1109/TASE.2021.3062979.

[25] Li Junqing, Liu Zhengmin, Li Chengdong, Zheng Zhixin. Improved artificial immune system algorithm for Type-2 fuzzy flexible job shop scheduling problem. IEEE Transactions on Fuzzy Systems , 2020, doi: 10.1109/TFUZZ.2020.3016225. 2020-TFS.pdf

[24] Li, Jun-qing (李俊青), Pan Quan-ke, Duan Pei-yong. An Improved Artificial Bee Colony Algorithm for Solving Hybrid Flexible Flowshop with Dynamic Operation Skipping, IEEE Transactions on Cybernetics, 46(6), 1311-1324 . 2016-TCYB.pdf

[23] Li, Jun-qing (李俊青), Pan Quan-ke, Mao Kun. A Hybrid Fruit Fly Optimization Algorithm for the Realistic Hybrid Flowshop Rescheduling Problem in Steelmaking Systems. IEEE Transactions on Automation Science and Engineering , 13(2): 932-949, 2016. 2016-TASE.pdf

[22] Li, Jun-qing (李俊青), Song Meixian., Wang Ling., Duan Peiyong., Han Yuyan., Sang Hongyan, Pan Quanke. Hybrid artificial bee colony algorithm for a parallel batching distributed flow shop problem with deteriorating jobs, IEEE Transactions on Cybernetics, 2020, 50(6): 2425-2439. . 2020-TCYB.pdf

[21] Li, Jun-qing (李俊青), Pan Quan-ke, Duan Pei-yong, Sang Hongyan. Solving multi-area environmental/economic dispatch by a Pareto-based chemical-reaction optimization algorithm. IEEE/CAA Journal of Automatica Sinica , 2019, 6(5): 1240-1250. 2019-JAS.pdf

[20] Li, Jun-qing (李俊青), Jia-wen Deng, Cheng-you Li, Yu-yan Han, Jie Tian, Biao Zhang, Cun-gang Wang. An Improved Jaya Algorithm for Solving the Flexible Job Shop Scheduling Problem with Transportation and Setup Times. Knowledge-Based Systems, 2020, doi: 10.1016/j.knosys.2020.106032. 2020-KBS.pdf

[19] Li, Jun-qing (李俊青), Tao, X.R., Jia B.X., Han Y.Y., Liu C., Duan P., Zheng Z.X., Sang H.Y.: Efficient multi-objective algorithm for the lot-streaming hybrid flowshop with variable sub-lots, Swarm. Evol. Comput, 52 (2020) 100600. https://doi.org/10.1016/j.swevo.2019.100600.2020-SWEO.pdf

[18] Li, Jun-qing (李俊青), Han, Y.Q., Duan, P.Y., Han, Y.Y., Niu, B., Li, C.D., Zheng, Z.X., Liu, Y.P.: Meta-heuristic algorithm for solving vehicle routing problems with time windows and synchronized visit constraints in prefabricated systems. J. Clean Prod. (2019). 2020-JCLP.pdf

[17] Li, Jun-qing (李俊青), S.C. Bai, P.Y. Duan, H.Y. Sang, Y.Y. Han, Z.X. Zheng, An improved artificial bee colony algorithm for addressing distributed flow shop with distance coefficient in a prefabricated system, International Journal of Production Research 57 (2019) 6922-6942. 2020-IJPR.pdf

[16] Li, Jun-qing (李俊青), Sang Hongyan(*), Han Yuyan, Wang Cungang, Gao Kaizhou, Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions. Journal of Cleaner Production, 181 (2018) 584-598. 2018-JCLP.pdf

[15] Li, Jun-qing (李俊青), Pan Q, Mao K. A discrete teaching-learning-based optimisation algorithm for realistic flowshop rescheduling problems. Engineering Applications of Artificial Intelligence, 2015, 37(1): 279-292. 2015-EAAI.pdf

[14] Li, Jun-qing(李俊青), and Pan Quanke. "Solving the large-scale hybrid flow shop scheduling problem with limited buffers by a hybrid artificial bee colony algorithm." Information Sciences, 2015, 316(20):487-502. 2015-INS.pdf

[13] Li, Jun-Qing(李俊青), Pan Quanke, and M. Fatih Tasgetiren. "A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities." Applied Mathematical Modelling 38.3 (2014): 1111-1132. 2014-AMM.pdf

[12] Li Junqing(李俊青), Pan Quanke, Kun Mao, P.N. Suganthan. Solving the steelmaking casting problem using an effective fruit fly optimisation algorithm. Knowledge-Based Systems, 2014, 72(12): 28-36. 2014-KBS.pdf

[11] Li, Jun-qing (李俊青), Pan Q, Wang F. A hybrid variable neighborhood search for solving the hybrid flow shop scheduling problem. Applied Soft Computing, 2014, 24: 63-77. 2014-ASC.pdf

[10] Li, Jun-qing (李俊青), Pan Q. Chemical-reaction optimization for solving fuzzy job-shop scheduling problem with flexible maintenance activities. International Journal of Production Economics, 145 (2013) 4–17. 2013-IJPE.pdf

[9] Li Junqing(李俊青) ∙ Pan Quanke ∙ Sheng-xian Xie. An effective shuffled frog-leaping algorithm for multi-objective flexible job shop scheduling problems. Applied Mathematics and Computation. 218(18): 9353-9371 (2012).

[8] Li Junqing(李俊青), Pan Quanke, Jing Chen. A hybrid Pareto-based local search algorithm for multi-objective flexible job shop scheduling problems. International Journal of Production Research, 50(4): 1063-1078, 2012.

[7] Li Junqing(李俊青), Pan Quanke: Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity. Appl. Soft Comput. 12(9): 2896-2912 (2012).

[6] Li Junqing(李俊青), Pan Quanke, Y. C. Liang. An effective hybrid tabu search algorithm for multi-objective flexible job shop scheduling problems. Computers and Industrial Engineering,2010, 59(4):647-662.

[5] 李俊青;杜宇;田杰;段培永;潘全科. 带运输资源约束柔性作业车间调度问题的人工蜂群算法. 电子学报, 2020, doi: 10.3969/j.issn.0372-2112.2020. 2021-电子学报.pdf

[4] 李俊青，潘全科. 求解模糊作业车间调度问题的混合优化算法. 机械工程学报, 2013, 49(23):142-149.

[3] 李俊青, 李文涵, 陶昕瑞, 杜宇, 韩玉艳, 潘全科. 时间约束混合流水车间调度问题综述, 控制理论与应用, 2020, 37(11) 2020: 2273-2290..

[2] 李俊青，潘全科，王玉亭. 多目标柔性车间调度的Pareto混合禁忌搜索算法.计算机集成制造系统. 2010, 16(7): 1419-1426.

[1] 李俊青，潘全科，王法涛. 求解混合流水线调度问题的离散人工蜂群算法, 运筹与管理, 2015, 24(1): 157-163.

三、代表性论文（通讯作者）

[36] Du Yu, Li, Junqing(通讯作者). A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling. International Journal of Production Economics, 268 (2024) 109102.

[35] Song Haonan, Li, Junqing(通讯作者), Du Zhaosheng, Yu Xin, Xu Ying, Zheng Zhixin, Li Jiake. A Q-learning driven multi-objective evolutionary algorithm for worker fatigue dual-resource-constrained distributed hybrid flow shop. Computers & Operations Research, 175, 106919, 2025.

[34] Xiaolong Chen, Li, Junqing(通讯作者), Zunxun Wang, Jiake Li, Kaizhou Gao. A genetic programming based cooperative evolutionary algorithm for flexible job shop with crane transportation and setup times. Applied Soft Computing, 169, 112614, 2025.

[33] Jiake Li, Li, Junqing(通讯作者), Ying Xu. HGNP: A PCA-based heterogeneous graph neural network for a family distributed flexible job shop. Computers & Industrial Engineering, 2025, 110855.

[32] Jia-ke Li, Rong-hao Li, Li, Junqing(通讯作者), Xin Yu, Ying Xu. A multi-dimensional co-evolutionary algorithm for multi-objective resource-constrained flexible flowshop with robotic transportation. Applied Soft Computing, 2025, 112689.

[31] Xinrui Wang, Li, Junqing(通讯作者), Yuanyuan Zhang, Kaizhou Gao, Zhixin Zheng, Jiake Li, Ying Xu. A bi-evolutionary cooperative multi-objective algorithm for blocking group flow shop with outsourcing option. Expert Systems With Applications, 258 (2024 ) 125101.

[30] Ting Li, Li, Junqing(通讯作者), Xiao-long Chen, Jia-ke Li. Solving distributed assembly blocking flowshop with order acceptance by knowledge-driven multiobjective algorithm. Engineering Applications of Artificial Intelligence, 137 (2024) 109220.

[29] Qing-qing Zeng, Li, Junqing(通讯作者), Rong-hao Li, Ti-hao Huang, Yu-yan Han, Hong-yan Sang. Improved NSGA-II for Energy-Efficient Distributed No-Wait Flow-Shop with Sequence-Dependent Setup Time. Complex & Intelligent Systems, (2023) 9:825–849, DOI :10.1007/s40747-022-00830-6.

[28] Ya-dian Geng, Li, Junqing(通讯作者). A knowledge-driven multiobjective algorithm for distributed hybrid flowshop with group and carryover setup in glass manufacturing systems. Computers & Industrial Engineering, 2023, 109325. https://doi.org/10.1016/j.cie.2023.109325

[27] Ronghao Li, Li, Junqing(通讯作者), Jinhua Li (李劲华), Peiyong Duan. A Collaboration-based Multi-objective Algorithm for Distributed Hybrid Flowshop Scheduling with Resource Constraints. 2023, Swarm and Evolutionary Computation, 83 (2023) 101409.

[26] Rui Qi, Li, Junqing(通讯作者), Xiaofeng Liu. A knowledge-driven multiobjective optimization algorithm for the transportation of assembled prefabricated components with multi-frequency visits. Automation in Construction, 2023, 152 (8) 104944.

[25] Xiaolong Chen, Li, Junqing(通讯作者), Ying Xu. Q-Learning based multi-objective immune algorithm for fuzzy flexible job shop scheduling problem considering dynamic disruptions, 2023, Swarm and Evolutionary Computation, 83 (2023) 101414.

[24] Xiaolong Chen, Li, Junqing(通讯作者), Yu Du. A hybrid evolutionary immune algorithm for fuzzy flexible job shop scheduling problem with variable processing speeds. Expert Systems with Applications, 2023, 233 (12) 120891, 120891. doi: 10.1016/j.eswa.2023.120891

[23] 亓瑞，李俊青(通讯作者). 基于问题性质的装配式预制件配送优化算法. 控制理论与应用, 41(2): 283-291, 2024.

[22] Yugang Liao, Li, Junqing(通讯作者), Shuwei Wei, Xiumei Xiao. Evolutionary Search via channel attention based parameter inheritance and stochastic uniform sampled training. Computer Vision and Image Understanding, 104000, 2024. (CCF-B)

[21] Yuanyuan Zhang, Li, Junqing(通讯作者), Ying Xu（许颖）,Peiyong Duan. Multi-population cooperative multi-objective evolutionary algorithm for sequence-dependent group flow shop with consistent sublots. Expert Systems with Applications, 237, 121594, 2024.

[20] Du Yu, Li, Junqing(通讯作者). A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling. International Journal of Production Economics, 268 (2024) 109102.

[19] Rong-hao Li, Li, Junqing(通讯作者), Jia-ke Li, Wei Ouyang, Li-jie Mei. A dimension-aware gaining-sharing knowledge algorithm for distributed hybrid flowshop scheduling with resource-dependent processing time. Complex & Intelligent Systems, doi: 10.1007/s40747-024-01484-2.

[18] Du, Yu; Li, Junqing(通讯作者); Li, Chengdong; Duan, Peiyong. A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times, IEEE Transactions on Neural Networks and Learning Systems, 2022, doi: 10.1109/TNNLS.2022.3208942.

[17] Du Yu, Li Junqing(李俊青，通讯作者), Chen Xiaolong, Duan Peiyong, Pan Quanke. A knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem. IEEE Transactions on Emerging Topics in Computational Intelligence,, 2022, doi: 10.1109/TETCI.2022.3145706

[16] Mou, J., Gao, K., Duan, P., Li Junqing(李俊青，通讯作者)., Garg, A., & Sharma, R. A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances. IEEE Transactions on Intelligent Transportation Systems, 2022, doi: 10.1109/TITS.2022.3183215.

[15] Niu Wei, Li, Junqing(通讯作者). A Two-stage Cooperative Evolutionary Algorithm for Energy-efficient Distributed Group Blocking Flow Shop with Setup Carryover in Precast Systems, Knowledge-Based Systems, doi: 10.1016/j.knosys.2022.109890.

[14] Rui Qi, Li Junqing(李俊青，通讯作者), Juan Wang, Hui Jin, &Yu-yan Han. QMOEA: A Q-learning-based multiobjective evolutionary algorithm for solving time-dependent green vehicle routing problems with time windows, Information Sciences, 2022(608), 178-201.

[13] Du Yu, Li Jun-qing(李俊青，通讯作者), Luo Chao, Meng Leilei. A hybrid estimation of distribution algorithm for distributed flexible job shop scheduling with crane transportations. Swarm and Evolutionary Computation, 2021, doi: 10.1016/j.swevo.2021.100861.

[12] Mei-xian Song, Li Jun-qing (李俊青，通讯作者), Yun-qi Han, Yu-yan Han, Li-li Liu, Qun Sun. Metaheuristics for solving the vehicle routing problem with the time windows and energy consumption in cold chain logistics. Applied Soft Computing, 2020, doi: 10.1016/j.asoc.2020.106561.

[11] Wenhan Li, Xiaolong Chen, Junqing Li(李俊青，通讯作者), Hongyan Sang, Yuyan Han, Shubo Du. An improved iterated greedy algorithm for distributed robotic flowshop scheduling with order constraints. Computers & Industrial Engineering, 2022, doi: 10.1016/j.cie.2021.107907.

[10] Niu wei, Li Junqing(李俊青，通讯作者), Jin Hui, Qi Rui, Sang Hongyan. Bi-objective Optimization Using Improved NSGA-II for Energy-Efficient Scheduling of Distributed Assembly Blocking Flow Shop. Engineering Optimization, doi: 10.1080/0305215X.2022.2032017.

[9] Xin-rui Tao; Li Jun-qing (李俊青，通讯作者); Ti-hao Huang; Peng Duan. Discrete imperialist competitive algorithm for the resource-constrained hybrid flowshop problem with energy consumption. Complex & Intelligent Systems, (2020) 10.1007/s40747-020-00193-w.

[8] Hui Yu, Li Junqing(李俊青，通讯作者), Xiao-Long Chen, Wei meng Zhang. A hybrid imperialist competitive algorithm for the outpatient scheduling problem with switching and preparation times.Journal of Intelligent & Fuzzy Systems, doi: 10.3233/JIFS-212024.

[7] Huang, T., Li Jun-qing(李俊青，通讯作者), Jia, B., Sang, H. (2021). CNV-MEANN: A Neural Network and Mind Evolutionary Algorithm-Based Detection of Copy Number Variations From Next-Generation Sequencing Data. Front. Genet. 12:1454. doi: 10.3389/fgene.2021.700874

[6] Yun-qi Han, Li Jun-qing (李俊青，通讯作者), Zhengmin Liu, Chuang Liu, Jie Tian. Metaheuristic algorithm for solving the multi-objective vehicle routing problem with time window and drones. International Journal of Advanced Robotic Systems, 2020, 17(2), 10.1177/1729881420920031.

[5] Hui Yu, Li Jun-qing (李俊青，通讯作者), Li-jing Zhang, Peng Duan. An imperialist competition algorithm using a global search strategy for physical examination scheduling. Applied Intelligence, 2020, 1-17.

[4] Liu Z, Xu H, Yu Y, Li Jun-qing (李俊青，通讯作者). Some q‐rung orthopair uncertain linguistic aggregation operators and their application to multiple attribute group decision making. International Journal of Intelligent Systems, 2019, 34(10): 2521-2555.

[3] Duan P, Li, J. Q(李俊青，通讯作者), Wang Y, Sang H, Jia B. Solving chiller loading optimization problems using an improved teaching-learning-based optimization algorithm. Optimal Control Applications & Methods. 2018, 39(1):65-77.

[2] Zheng ZX, Li J(李俊青，通讯作者). Optimal chiller loading by improved invasive weed optimization algorithm for reducing energy consumption, Energy and Buildings, 161 (2018) 80–88, 2018.

[1] Zheng ZX, Li, JQ(李俊青，通讯作者), Duan PY. Optimal chiller loading by improved artificial fish swarm algorithm for energy saving. Mathematics and Computers in Simulation, 2019, 155: 227-243.

四、代表性论文（其他）

[6] H. Li, K. Gao, P.-Y. Duan, J.-Q. Li and L. Zhang, "An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, doi: 10.1109/TSMC.2022.3219380.

[5] Niu, B., Li, H., Zhang, Z., Li, J., Hayat, T., & Alsaadi, F. E. (2018). Adaptive neural-network-based dynamic surface control for stochastic interconnected nonlinear nonstrict-feedback systems with dead zone. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(7), 1386-1398.

[4] Li, C., Yi, J., Wang, H., Zhang, G., & Li, J. (2020). Interval Data Driven Construction of Shadowed Sets with Application to Linguistic Word Modelling. Information Sciences, 507 (2020) 503-521.

[3] Ben Niu, Yanjun Liu, Wanlu Zhou, Haitao Li, Peiyong Duan, Junqing Li. Multiple Lyapunov Functions for Adaptive Neural Tracking Control of Switched Nonlinear Nonlower-Triangular Systems, IEEE transactions on cybernetics, 2019, doi: 10.1109/TCYB.2019.2906372

[2] Sun, J., Miao, Z., Gong, D., Zeng, X. J., Li, J., & Wang, G. (2020). Interval Multiobjective Optimization With Memetic Algorithms. IEEE transactions on cybernetics, 2020, doi: 10.1109/TCYB.2019.2908485.

[1] Niu, B., Duan, P., Li, J., & Li, X. (2020). Adaptive Neural Tracking Control Scheme of Switched Stochastic Nonlinear Pure-Feedback Nonlower Triangular Systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, doi: 10.1109/TSMC.2019.2894745.

五、专著

[1] 李俊青, 李佳珂, 郑元杰, 陈庆达. 分布式流水车间调度与算法, 科学出版社, 2025, ISBN: 978-7-03-081096-0.

[2] 李俊青，段培永，潘全科，刘闯，张映玉，郑志新，孙群. 柔性作业车间调度问题及其智能优化算法(英文). 科学出版社, 2018.11

[3] 李俊青，潘全科，刘闯, 钢铁生产调度问题及其人工蜂群算法研究,科学出版社,320千字, 2017

[4] 李俊青, 李荣昊. 资源约束混合流水车间调度优化方法, 中国水利水电出版社, 141千字, 2024.12, ISBN: 978-7-5226-2920-9.

六、授权发明专利

[1] 潘全科，李俊青，毛坤. 一种流水车间重调度方法, 2013107191113，位次2，专利号：ZL201310719111.3，专利申请日：2013.12.20，授权日：2016.8.17，证书号：20183522

[2] 李俊青.一种冷风机参数配置优化方法, 专利号，201611131651.X，授权日期：2019.11.5，授权专利号：ZL201611131651.X

[3] 李俊青，段培永，桑红燕，潘全科. 一种多目标资源配置方法, 专利号：201610330606.0, 授权日期： 2020.7.24 发文序号：2020071600004880，授权专利号：ZL201610330606.0

[4] 李俊青，段培永，桑红燕，潘全科. 一种多目标资源配置系统，申请号：201610330192.1, 授权日期：2020.7.9， 发文序号：2020060401185530，授权专利号：ZL201610330192.1

[5] 李俊青, 宋美娴, 郑志新. 一种带时间窗的冷链物流路径优化方法，授权日期：2020.12.02，授权专利号：ZL201910290492.5.

[6] 李庆华，李俊青. 一种分布式装配式置换流水车间调度优化方法及系统，授权日期：2020.11.20，授权专利号：ZL201911047259.0

[7] 李俊青, 韩云琦, 段培永. 带时间窗的装配式建筑预制件配送路径优化方法及系统，授权日期：2021.6.25，授权专利号：ZL201811548831.7

七、获得学术奖励

[9] 2024年，山东省自然科学二等奖，位次2.

[8] 2021年，山东省自然科学二等奖，位次2.

[7] 2019年，江苏省科学技术奖二等奖，位次4，（No. 2018-2-30-R4）.

[6] 2016年，山东高等学校优秀科研成果奖一等奖，位次1,证书编号：2016BK10160.

[5] 2014年，辽宁省自然科学学术成果二等奖，位次1, 证书编号：2014-LNL0279.

[4] 李俊青（1/4），山东省教育厅，山东高等学校优秀科研成果奖，一等奖，2014, 证书编号：2014BZ10154.

[3] 2017年，山东高等学校优秀科研成果奖二等奖，“钢铁生产调度中混合群体智能优化算法研究”，位次1.

[2] 2016, A discrete teaching-learning-based optimization algorithm for realistic flowshop rescheduling problems，辽宁省自然科学学术成果奖 三等奖, 证书编号：161206001411825.

[1] 李俊青（1/5），新型混合智能算法及其车间调度优化研究，山东省软科学优秀成果奖励委员会，山东软科学优秀成果奖，三等奖，2012，证书编号：RK12-09-03-59-01.