Academic Qualification
Ph.D. in School of Electronic and Electrical Engineering, Nanyang Technological University
Master in Yangzhou University
Bachelor in Liaocheng University
Teaching Area
Artificial Intelligence
Management Science
Research Area
Intelligent Optimization
Evolutionary computation
Scheduling and Optimization
Machine Learning
Reinforcement learning
Deep learning
Complex system modelling
Professional Services
Associate Editor, IEEE Transactions on Intelligence Transportation Systems, since 2022
Associate Editor, Swarm and Evolutionary Computations, since 2019
Associate Editor, Expert Systems with Application, since 2022
Associate Editor, IET Collaborative Intelligent Manufacturing, since 2021
Working Experience
Sep. 2019 ~ present, Assistant Professor, Department of Engineering Science, Faculty of Innovation Engineering, MUST
Apr. 2015 ~ Apr. 2018, Research Fellow, School of Electronic and Electrical Engineering, Nanyang Technological University
FEB.2012 ~ DEC. 2012, Research Associate, School of Electronic and Electrical Engineering, Nanyang Technological University
Academic Publication (selected)
2024
1. H. Yu, K. Gao, Z. Ma, and L. Wang, “Exact and deep Q-network assisted swarm intelligence methods for scheduling multi-Objective heterogeneous unmanned surface vehicles,” IEEE Transactions on Evolutionary Computation, 2024, doi: 10.1109/TEVC.2024.3415368. (SCI一区)
2. H. Yu, K. Gao*, N. Wu, M. Zhou, P. N. Suganthan and S. Wang, "Scheduling Multiobjective Dynamic Surgery Problems via Q-Learning-Based Meta-Heuristics," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 54, no. 6, pp. 3321-3333, June 2024. (SCI一区)
3. Z. Lin, K. Gao, N. Wu, and P. N. Suganthan, “Scheduling eight-phase urban traffic light problems via ensemble meta-heuristics and Q-learning based local search,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 12, pp. 14415–14426, 2023.
4. Z. Lin, K. Gao, N. Wu, and P. N. Suganthan, “Problem-Specific Knowledge Based Multi-Objective Meta-Heuristics Combined Q-Learning for Scheduling Urban Traffic Lights With Carbon Emissions,” IEEE Transactions on Intelligent Transportation Systems, 2024, doi: 10.1109/TITS.2024.3397077.
5. Yaxian Ren, Kaizhou Gao*, Yaping Fu, Dachao Li, Ponnuthurai Nagaratnam Suganthan, Ensemble artificial bee colony algorithm with Q-learning for scheduling Bi-objective disassembly line, Applied Soft Computing, Volume 155, 2024, 111415. (SCI一区)
6. Kaizhou Gao*, Minglong Gao, Mengchu Zhou, Zhenfang Ma, Artificial intelligence algorithms in unmanned surface vessel task assignment and path planning: A survey, Swarm and Evolutionary Computation, Volume 86, 2024, 101505. (SCI一区)
7. Yaping Fu, Xiaomeng Ma, Kaizhou Gao*, Hongfeng Wang, Ali Sadollah, L.Y. Chen, Multi-objective migrating birds optimization for solving stochastic home health care routing and scheduling problems considering caregiver working time constraints, Swarm and Evolutionary Computation, Volume 85, 2024, 101484. (SCI一区)
8. L. Zhong, W. Li*, K. Gao*, L. He and Y. Zhou, "An Improved NSGAII for Integrated Container Scheduling Problems With Two Transshipment Routes," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3388468. (SCI一区)
9. Zhengpei Zhang, Yaping Fu*, Kaizhou Gao*, Hui Zhang, Lei Wang, A cooperative evolutionary algorithm with simulated annealing for integrated scheduling of distributed flexible job shops and distribution, Swarm and Evolutionary Computation, Volume 85, 2024, 101467. (SCI一区)
10. Pei Liang, Yaping Fu*, Kaizhou Gao*, Multi-product disassembly line balancing optimization method for high disassembly profit and low energy consumption with noise pollution constraints, Engineering Applications of Artificial Intelligence, Volume 130, 2024, 107721. (SCI二区)
11. Ma Z., Gao K.*, Yu H., Wu N. Solving Heterogeneous USV Scheduling Problems by Problem-Specific Knowledge Based Meta-Heuristics with Q-Learning. Mathematics 2024, 12, 339. (SCI二区)
12. Liu F., K. Gao*, et al.: Ensemble evolutionary algorithms equipped with Q-learning strategy for solving distributed heterogeneous permutation flowshop scheduling problems considering sequence-dependent setup time. IET Collab. Intell. Manuf. e12099 (2024). https://doi.org/10.1049/cim2.12099 (SCI)
13. Y. Pan, K. Gao, Z. Li and N. Wu, "A Novel Evolutionary Algorithm for Scheduling Distributed No-Wait Flow Shop Problems," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 54, no. 6, pp. 3694-3704, June 2024. (SCI一区)
2023
14. 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, 53(5): 2684-2693, 2023, doi: 10.1109/TSMC.2022.3219380. (ESI Hot paper)
15. Xiaomeng Ma, Yaping Fu, Kaizhou Gao, Hui Zhang, Jianhui Mou, A knowledge-based multi-objective evolutionary algorithm for solving home health care routing and scheduling problems with multiple centers, Applied Soft Computing, 2023, 110491.
16. Yaxian Ren, Kaizhou Gao, Yaping Fu, Hongyan Sang, Dachao Li, Zile Luo, A novel Q-learning based variable neighborhood iterative search algorithm for solving disassembly line scheduling problems, Swarm and Evolutionary Computation, Volume 80, 2023, 101338.
17. Hui Yu, Kai-Zhou Gao, Zhen-Fang Ma, Yu-Xia Pan, Improved meta-heuristics with Q-learning for solving distributed assembly permutation flowshop scheduling problems, Swarm and Evolutionary Computation, Volume 80, 2023, 101335.
18. Ziye Zhao, Xiaohui Chen, Youjun An, Yinghe Li, Kaizhou Gao, A property-based hybrid genetic algorithm and tabu search for solving order acceptance and scheduling problem with trapezoidal penalty membership function, Expert Systems with Applications, Volume 218, 2023, 119598.
19. Yushuang Hou, Hongfeng Wang, Yaping Fu, Kaizhou Gao, Hui Zhang, Multi-Objective brain storm optimization for integrated scheduling of distributed flow shop and distribution with maximal processing quality and minimal total weighted earliness and tardiness, Computers & Industrial Engineering, Volume 179, 2023, 109217.
20. Youjun An, Xiaohui Chen, Kaizhou Gao, Lin Zhang, Yinghe Li, Ziye Zhao, Integrated optimization of real-time order acceptance and flexible job-shop rescheduling with multi-level imperfect maintenance constraints, Swarm and Evolutionary Computation, Volume 77, 2023, 101243.
2022
21. X. Ma, Y. Fu, K. Gao*, et al. Integration routing and scheduling for multiple home health care centers using a multi-objective cooperation evolutionary algorithm with stochastic simulation. Swarm and Evolutionary Computation, 2022, 75: 101175.
22. Y. Fu, F. Ding, Z. Mu, C. Sun, K. Gao, Integrating scheduling and routing decisions into home health care operation with skill requirements and uncertainties. Journal of Simulation, 2022: 1-24.
23. R. Jin, M. Wu, K. Wu, K. Gao, Z. Chen, X. Li, Position encoding based convolutional neural networks for machine remaining useful life prediction. IEEE/CAA Journal of Automatica Sinica, 2022, 9(8): 1427-1439.
24. Y. An, X. Chen, K. Gao*, et al. A hybrid multi-objective evolutionary algorithm for solving an adaptive flexible job-shop rescheduling problem with real-time order acceptance and condition-based preventive maintenance. Expert Systems with Applications, 2023, 212: 118711.
25. Y. Zhang, Y. Hu, X. Gao, K. Gao, Zhang, W. An embedded vertical‐federated feature selection algorithm based on particle swarm optimisation. CAAI Transactions on Intelligence Technology, 2022.
26. Z. He, K. Wang, H. Li, H. Song, Z. Lin, K. Gao, A. Sadollah. Improved Q‐learning algorithm for solving permutation flow shop scheduling problems. IET Collaborative Intelligent Manufacturing, 2022, 4(1): 35-44.
27. Y. Z. Li, Q. K. Pan, X. He, H. Y. Sang, K. Z. Gao, Jing, X. L. The distributed flowshop scheduling problem with delivery dates and cumulative payoffs. Computers & Industrial Engineering, 2022, 165: 107961.
28. Y. An, Z. Zhao, X. Chen, Y. Li, K. Gao, A Property-Based Hybrid Genetic Algorithm and Tabu Search for Solving Order Acceptance and Scheduling Problem with Trapezoidal Penalty Membership Function. Available at SSRN 4215297.
29. Z. Li, H. Sang, Q. Pan, K. Gao, Y. Han, J. Li, Dynamic AGV scheduling model with special cases in matrix production workshop. IEEE Transactions on Industrial Informatics, 2022.
30. L. Meng, B. Zhang, Y. Ren, H. Sang, K. Gao, Mathematical Formulations for Asynchronous Parallel Disassembly Planning of End-of-Life Products. Mathematics, 2022, 10(20): 3854.
31. J. Mou, P. Duan*, L. Gao, Q. Pan, K.Z. Gao*, AK Singh, Biologically Inspired Machine Learning-Based Trajectory Analysis in Intelligent Dispatching Energy Storage System, IEEE Transactions on Intelligent Transportation Systems, 2022, doi: 10.1109/TITS.2022.3154750.
32. J. Mou, K.Z. Gao*, P. Duan, J. Li*, A. Garg and R. Sharma, "A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances," in IEEE Transactions on Intelligent Transportation Systems, 2022, doi: 10.1109/TITS.2022.3183215. (ESI Hot paper)
33. Y. Pan, K. Gao*, Z. Li and N. Wu, "Solving Biobjective Distributed Flow-Shop Scheduling Problems With Lot-Streaming Using an Improved Jaya Algorithm," IEEE Transactions on Cybernetics, 53(6): 3818-3828, 2023. doi: 10.1109/TCYB.2022.3164165. https://ieeexplore.ieee.org/document/9762895
34. Y. Pan, K. Gao, Z. Li and N. Wu, "Improved Meta-Heuristics for Solving Distributed Lot-Streaming Permutation Flow Shop Scheduling Problems," IEEE Transactions on Automation Science and Engineering, Feb 2022, doi: 10.1109/TASE.2022.3151648. https://ieeexplore.ieee.org/document/9722368
35. Y. An, X. Chen, K. Gao, Y. Li and L. Zhang, "Multiobjective Flexible Job-Shop Rescheduling With New Job Insertion and Machine Preventive Maintenance," IEEE Transactions on Cybernetics, Mar 2022, doi: 10.1109/TCYB.2022.3151855. https://ieeexplore.ieee.org/document/9733957
36. Junqing Li, Yu Du, Kaizhou Gao, P.N. Suganthan. A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem, IEEE Transactions on Automation Science and Engineering, Mar, 2021. DOI: 10.1109/TASE.2021.3062979
37. Guoxing Wen, Wei Hao, Weiwei Feng, Kaizhou Gao, Optimized Backstepping Tracking Control Using Reinforcement Learning for Quadrotor Unmanned Aerial Vehicle System, IEEE Transactions on Systems, Man, and Cybernetics: Systems, September 2021. DOI: 10.1109/TSMC.2021.3112688
38. PW Shaikh, M El-Abd, M Khanafer, KZ Gao, A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem, IEEE Transactions on Intelligent Transportation Systems, 23(1): 48-63, Jan 2022. (ESI high cited paper)
39. Leilei Meng, Kaizhou Gao*, Yaping Ren, Biao Zhang, Hongyan Sang, Zhang Chaoyong, “Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times,” Swarm and Evolutionary Computation, 71: 101058, 2022.
40. Yaping Fu, Yushuang Hou, Kaizhou Gao*, et al. Modelling and Scheduling Integration of Distributed Production and Distribution Problems via Black Widow Optimization. Swarm and Evolutionary Computation, Nov. 2021. https://doi.org/10.1016/j.swevo.2021.101015
41. Yushuang Hou, Yaping Fu*, Kaizhou Gao*, Hui Zhang, Ali Sadollahd, Modelling and optimization of integrated distributed flow shop scheduling and distribution problems with time windows. Expert Systems with Application, 187: 115827, 2022.
42. Ren Wang, Mengchu Zhou, Kaizhou Gao et al. Personalized routing system based on driver preference, Sensors, 22(1):11, Dec. 2022.
2021
43. Zicheng Liu, Naiqi Wu, Kaizhou Gao*, Urban Traffic Light Control Considering Capacity Difference Between Public Bus and Private Vehicles, IEEE Access, PP(99):1-1, October 2021.
44. Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao*, Ling Wang*. Distributed Scheduling Problems in Intelligent Manufacturing Systems. Tsinghua Science and Technology, 2021, 26(5): 625-645.
45. Pei Liang, Yaping Fu, Kaizhou Gao, Hao Sun, An enhanced group teaching optimization algorithm for multi-product disassembly line balancing problems. Complex & Intelligent Systems, Aug 2021. DOI https://doi.org/10.1007/s40747-021-00478-8
46. Yuanzhen Li, Quanke Pan, Kaizhou Gao, M.F. Tasgetiren, Biao Zhang, Junqing Li. A green scheduling algorithm for the distributed flowshop problem, Applied Soft Computing, 109, Sep. 2021, 107526.
47. Yuan Zhao, Hong Liu, Kaizhou Gao, An evacuation simulation method based on an improved artificial bee colony algorithm and a social force model. Applied Intelligence, 51: 100-123, Jan 2021.
48. YY Niu, YP Zhang, ZG Cao, Kaizhou Gao, JH Xiao, W Song, FW Zhang, MIMOA: A Membrane-Inspired Multi-Objective Algorithm for Green Vehicle Routing Problem with Stochastic Demands, Swarm and Evolutionary Computation, 60, 100767, Feb 2021.
2020
49. KZ Gao, ZM He, Y Huang, PY Duan, PN Suganthan, A survey on meta-heuristics for solving disassembly line balancing, planning and scheduling problems in remanufacturing, Swarm and Evolutionary Computation, 57, Sep 2020.
50. KZ Gao, FJ Yang, JQ Li, HY Sang, JP Luo, Improved Jaya algorithm for flexible job shop rescheduling problems, IEEE Access, 8: 86915 - 86922, May 2020.
51. A Sadollah, KZ Gao, JH Kim, Memetic computing for imprecise solution of T-shaped heat transfer fins, Engineering Optimization, Aug 2020, DOI: 10.1080/0305215X.2020.1806256.
52. Xin-Rui Tao, Jun-Qing Li, Yu-Yan Han, Peng Duan, Kaizhou Gao, Discrete imperialist competitive algorithm for the resource-constrained hybrid flowshop problem. Journal of Industrial and Production Engineering, 37(7): 345-359, Oct 2020.
53. ZH Chen, M Wu, KZ Gao, et al, A Novel Ensemble Deep Learning Approach for Sleep-Wake Detection Using Heart Rate Variability and Acceleration, IEEE Transactions on Emerging Topics in Computational Intelligence, June, 2020, DOI: 10.1109/TETCI.2020.2996943.
54. YY Han, JQ Li, HY Sang, YP Liu, KZ Gao, QK Pan, Discrete evolutionary multi-objective optimization for energy-efficient blocking flow shop scheduling with setup time, Applied Soft Computing, May 2020, DOI: 10.1016/j.asoc.2020.106343.
55. ZG Cao, HL Guo, W Song, KZ Gao, LJ Kang, XX Zhang, QL Wu, Improving the Performance of Transportation Networks: A Semi-Centralized Pricing Approach, IEEE Transactions on Intelligent Transportation Systems, Apr. 2020, DOI: 10.1109/TITS.2020.2991759.
56. L Zhang, ZH Chen, W Cui, B Li, C Chen, ZG Cao, KZ Gao, WiFi-Based Indoor Robot Positioning Using Deep Fuzzy Forests, IEEE Internet of Things Journal, Apr. 2020, DOI：10.1109/JIOT.2020.2986685.
57. ZG Cao, HL Guo, W Song, KZ Gao, ZH Chen, L Zhang, XX Zhang, Using reinforcement learning to minimize the probability of delay occurrence in transportation, IEEE Transactions on Vehicular Technology, 69(3): 2424-2436, Jan 2020.
58. J. Lin, L. Zhu, KZ Gao, A genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem, Expert Systems with Applications, 140, 112915, 2020.
59. KZ Gao, Y Huang, A Sadollah, L Wang, A review of energy-efficient scheduling in intelligent production systems, Complex & Intelligent Systems, 6: 237-249, July 2020. (ESI high cited paper)
2019
60. KZ Gao, Y Zhang, R Su, FJ Yang, PN Suganthan, MC Zhou, Solving Traffic signal scheduling problems in heterogeneous traffic network by using meta-heuristics, IEEE Transactions on Intelligent Transportation Systems, 20 (9), 3272-3282, Sep 2019.
61. KZ Gao, Y Zhang, Y Zhang, R Su, PN Suganthan, Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems, IEEE Transactions on Intelligent Transportation Systems, 20 (7), 2618-2629, July 2019.
62. KZ Gao, F.J. Yang, M.C. Zhou, Q.K. Pan, P. N. Sugnathan, Flexible job shop rescheduling for new job insertion by using discrete Jaya algorithm. IEEE Transactions on Cybernetics, vol. 49, no. 5, pp: 1944-1955, May 2019. (ESI high cited paper)
63. KZ Gao, ZG Cao, L Zhang et al., A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems, IEEE/CAA Journal of Automatica Sinica, 6(4), 904-916, July 2019. (ESI high cited paper)
64. WH Li, JQ Li, KZ Gao et al., Solving robotic distributed flowshop problem using an improved iterated greedy algorithm, International Journal of Advanced Robotic Systems, 16(5), Article Number: 1729881419879819 Published: SEP 2019
65. J. Li, Q. Pan, P. Duan, H. Sang, KZ Gao. Solving multi-area environmental/economic dispatch by Pareto-based chemical-reaction optimization algorithm. IEEE/CAA Journal of Automatica Sinica, 6(5): 1240-1250, Sep 2019.
66. A Sadollah, KZ Gao, Y Zhang, Y Zhang, R Su, Management of traffic congestion in adaptive traffic signals using a novel classification-based approach, Engineering Optimization, 51(9), 1509-1528, Sep 2019.
67. Y Zhang, KZ Gao, YC Zhang, R Su, Traffic light scheduling for pedestrian-vehicle mixed-flow networks, IEEE Transactions on Intelligent Transportation Systems, 20(4): 1468-1483, Apr 2019.
68. Y Huang, K Wang, KZ Gao*, T Qu, H Liu, Jointly optimizing microgrid configuration and energy consumption scheduling of smart homes, Swarm and Evolutionary computation, 48, 251-261, Feb 2019.
69. QQ Wang, H Liu, KZ Gao, Le Zhang, Improved multi-agent reinforcement learning for path planning based crowd simulation, IEEE Access, 7, 73841-73855, 2019.
70. S.N. Wang, H. Liu, KZ Gao, J.X. Zhang, A multi-species artificial bee colony algorithm and its applications for crowd simulation, IEEE Access, 7: 2549-2558, 2019.
71. H.Y. Sang, Q.K. Pan, J.Q. Li, P. Wang, Y.Y. Han, KZ Gao, P Duan, Effective invasive weed optimization algorithms for distributed assembly permutation flow shop problem with total flowtime criterion, Swarm and evolutionary computation, 44, 64-73, 2019.
2018
72. KZ Gao, L. Wang. Discrete harmony search algorithm for scheduling and rescheduling the re-processing problems in remanufacturing: A case study. Engineering Optimization, 50(6): 965-981, 2018.
73. F. Yang, KZ Gao, I.W. Simon, Yuting Zhu, Rong Su. Decomposition methods for manufacturing system scheduling: a survey, IEEE/CAA Journal of Automatica Sinica, 5(2): 389-400, 2018.
74. FJ Yang, Y Qiao, KZ Gao, NQ Wu, YT Zhu, IW Simon, R Su, Efficient Approach to Scheduling of Transient Processes for Time-Constrained Single-Arm Cluster Tools With Parallel Chambers, IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2018.2852724, 2018.
75. F. Yang, N. Wu, KZ Gao. Efficient Approach to Cyclic Scheduling of Single-arm Cluster Tools with Chamber Cleaning Operations and Wafer Residency Time Constraint, IEEE Transactions on Semiconductor Manufacturing, 31(2): 196-205, 2018.
76. JQ Li, HY Sang, YY Han, CG Wang, KZ Gao, efficient multi-objective optimization algorithm for hybrid flow shop scheduling problem with setup energy consumptions, Journal of Cleaner Production, 181: 584-598, 2018. (ESI high cited paper)
77. JP. Luo, Y Yang, X. Li, QQ Liu, MR Chen, KZ Gao, A decomposition-based multi-objective evolutionary algorithm with quality indicator, Swarm and Evolutionary Computation, 39: 339-355, 2018.
78. JP. Luo, Y Yang, QQ Liu, X. Li, MR Chen, KZ Gao, A new hybrid memetic multi-objective optimization algorithm for multi-objective optimization, Information Sciences, 448: 164-186, 2018.
2017
79. KZ Gao, A. Sadollah, Y. Zhang, R. Su. Jaya, harmony search and water cycle algorithms for solving large-scale real-life urban traffic light scheduling problem. Swarm and Evolutionary computation, 37: 58-72, 2017.
80. A. Sadollah, N. Yadav, KZ Gao, R. Su. Metaheuristic optimization methods for approximate solving of singular boundary value problems, Journal of Experimental & Theoretical Artificial, 29: (4): 823-842, 2017.
81. Quan-Ke Pan, Liang Gao, Xin-Yu Li, KZ Gao. Effective metaheuristics for scheduling a hybrid flow shop with sequence-dependent setup times. Applied mathematics and computation, 303: 89-112, 2017. (ESI high cited paper)
82. J. Li, J. Wang, Q. Pan, P. Duan, H. Sang, KZ Gao. A hybrid artificial bee colony for optimizing a reverse logistics network system. Soft Computing, 21(20): 6001-6018, 2017.
2016
83. KZ Gao, et al. Optimizing Urban Traffic Light Scheduling Problem Using Harmony Search with Ensemble of Local Search. Applied Soft Computing, 48: 359-372, 2016.
84. KZ Gao, P. N. Suganthan, Q.K. Pan, M. F. Tasgetiren, A. Sadollah. Artificial Bee Colony Algorithm for Scheduling and Rescheduling Fuzzy Flexible Job Shop Problem with New Job Insertion. Knowledge-based systems, 109: 1-16, 2016.
85. KZ Gao, P.N. Suganthan, Tay Jin Chua et al. Discrete Harmony Search Algorithm for Flexible Job Shop Scheduling Problem with Weighted Combination of Multiple Objectives, Journal of Intelligent Manufacturing, 27(2): 363-374, 2016. (ESI high cited paper)
86. Mehmet Fatih Tasgetiren, Quan-Ke Pan, Damla Kizilay, KZ Gao. A Variable Block Insertion Heuristic for the Blocking Flowshop Scheduling Problem with Total Flowtime Criterion, Algorithms, 9(4): 71, 2016.
87. KZ Gao, et al. An improved artificial bee colony algorithm for multi-objective flexible job shop scheduling problem with fuzzy processing time. Expert systems with applications, 65: 52-67, 2016.
2015 and before
88. KZ Gao, P.N. Suganthan, Q.K. Pan, M.F. Tasgetiren. Effective ensembles of heuristics for scheduling multi-objective flexible job shop problem with new job insertion. Computer & Industrial Engineering, 90: 107-117, 2015.
89. KZ Gao, P.N. Suganthan, Q. K. Pan, M.F. Tasgetiren. An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time. International Journal of Production Research, 53 (19), 5896-5911, 2015.
90. KZ Gao, P. N. Suganthan, T.J. Chua, C. S. Chong, T. X. Cai, Q. K. Pan. A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion. Expert systems with applications, 42(21), 7652-7663, 2015.
91. KZ Gao, P.N. Suganthan, Tay Jin Chua, et al. Pareto-based Grouping Discrete Harmony Search Algorithm for Multi-objective Flexible Job Shop Scheduling, Information Sciences, 289, 76-90,2014.
92. KZ Gao, Q. Pan, P.N. Suganthan, J. Li. Effective heuristics for the no-wait flow shop scheduling problem with total flow time minimization. International Journal of Advanced Manufacturing Technology, 66(9-12):683-692, 2013.
93. KZ Gao, Q. Pan, J. Li, Y. Wang, Liang Jing. A novel hybrid harmony search algorithm for the no-wait flow shop scheduling problems with total flow time criteria. Asia-Pacific Journal of Operational Research, 29(2):12500121-23, 2012.
94. KZ Gao, Q. Pan, J. Li. Discrete harmony search algorithm for the no-wait flow shop scheduling problem with total flow time criterion. International Journal of Advanced Manufacturing Technology, 56(5):683-692, 2011.
95. J. Li, Q. Pan, KZ Gao. Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems. International Journal of Advanced Manufacturing Technology, 55: 1159-1169, 2011.
96. Y. Wang, J. Li, KZ Gao, Q. Pan. Memetic algorithm based on improved Inver-over operator and lin-kernighan local search for the Euclidean traveling salesman problem. Computers & Mathematics with Applications, 62:2743-2754, 2011.
Research Grants
2022.01 -- 2025.12 Problem specific knowledge based intelligent scheduling and rescheduling for uncertain remanufacturing (NSFC)
2021.10 -- 2024.10 Learning based collaborative intelligent scheduling and rescheduling for remanufacturing with uncertains (FDCT)
2017.01 -- 2019.12 Ensembles of discrete intelligent algorithms for re-manufacturing scheduling with complex constraints (NSFC)
2023.01 -- 2025.12 Problem-specific knowledge and learning based distributed intelligent manufacturing scheduling (Guangdong Basic and Applied Basic Research Foundation)
2019.01 -- 2020.12 Research funding from Macau University of Science and Technology (MUST)
2021.09 -- 2024.09 USV intelligent collaborative and autonomous task allocation: theories and applications (Zhuhai Industry-University-Research Project with Hongkong and Macao)
Professional Certification and Awards
Best Research Output Award in 2024
World’s Top 2% Scientists in 2023
Shandong Science and Technology Award, Natural Science Award, Second Prize in 2023
World’s Top 2% Scientists in 2022
Norbert Wiener Review Award by IEEE/CAA Journal of Automatica Sinica in 2022
Excellent Paper Award by TSINGHUA Science and Technologyin 2022
World’s Top 2% Scientists in 2021
Shandong Science and Technology Award, Natural Science Award, Second Prize in 2021
Shandong Provincial Higher Education Science and Technology Award in 2020
Excellent Paper Award of the 4th Conference on Intelligent Optimization and Scheduling in 2020
Student Awards
Yu Hui --- Excellent Paper Award of the 7th Conference on Intelligent Optimization and Scheduling in 2024
Lin Zhongjie --- Excellent Paper Award of the 7th Conference on Intelligent Optimization and Scheduling in 2024
Pan Yuxia --- Excellent Paper Award of the 5th Conference on Intelligent Optimization and Scheduling in 2023
Professional Society Membership
Member, IEEE
Senior Member, Intelligent Simulation Optimization and Scheduling Committee of China Simulation Fdederation
