Publications


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Journal Articles

  1. Song, Y., Ou, J., Pedrycz, W., Suganthan, P. N., Wang, X., Xing, L., & Zhang, Y. (2024). Generalized Model and Deep Reinforcement Learning-Based Evolutionary Method for Multitype Satellite Observation Scheduling. IEEE Transactions on Systems, Man, and Cybernetics: Systems. [pdf]
  2. Wei, L., Chen, M., Xing, L., Wan, Q., Song, Y., Chen, Y., & Chen, Y. (2024). Knowledge-transfer based genetic programming algorithm for multi-objective dynamic agile earth observation satellite scheduling problem. Swarm and Evolutionary Computation, 101460. [pdf]
  3. Huang, J., Li, J., Du, Y., Song, Y., Wu, J., Yao, F., & Wang, P. (2023). Research of a Multi-Level Organization Human Resource Network Optimization Model and an Improved Late Acceptance Hill Climbing Algorithm. Mathematics, 11(23), 4813. [pdf]
  4. Liu, S., Wang, J., Wang, R., Zhang, Y., Song, Y., & Xing, L. (2023). Data-driven dynamic pricing and inventory management of an omni-channel retailer in an uncertain demand environment. Expert Systems with Applications, 122948. [pdf]
  5. Wu, J., Cheng, L., Chu, S., & Song, Y. (2024). An autonomous coverage path planning algorithm for maritime search and rescue of persons-in-water based on deep reinforcement learning. Ocean Engineering, 291, 116403. [pdf]
  6. Tan, W., Tian, H., Song, Y., & Duan, X. (2023). Impact of Allee and fear effects in a fractional order prey–predator system with group defense and prey refuge. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(10). [pdf]
  7. Song, Y., Suganthan, P. N., Pedrycz, W., Ou, J., He, Y., Chen, Y., & Wu, Y. (2023). Ensemble reinforcement learning: A survey. Applied Soft Computing, 110975. [pdf]
  8. Liu, J., Wang, T., Yao, F., Pedrycz, W., Song, Y.*, & He, R. (2024). Assessing growth potential of careers with occupational mobility network and ensemble framework. Engineering Applications of Artificial Intelligence, 127, 107306. [pdf]
  9. Huang, Y., Luo, A., Chen, T., Zhang, M., Ren, B., & Song, Y. (2023). When architecture meets RL+ EA: A hybrid intelligent optimization approach for selecting combat system-of-systems architecture. Advanced Engineering Informatics, 58, 102209. [pdf]
  10. Wang, H., Yang, W., Li, J., Ou, J., Song, Y., & Chen, Y. (2023). An improved heterogeneous graph convolutional network for job recommendation. Engineering Applications of Artificial Intelligence, 126, 107147. [pdf]
  11. Song, Y., Ou, J., Suganthan, P. N., Pedrycz, W., Yang, Q., & Xing, L. (2023). Learning Adaptive Genetic Algorithm for Earth Electromagnetic Satellite Scheduling. IEEE Transactions on Aerospace and Electronic Systems. [pdf]
  12. Feng, Q., Zhang, Y., Sun, B., Guo, X., Fan, D., Ren, Y., Song, Y., Wang, Z. (2023). Multi-level predictive maintenance of smart manufacturing systems driven by digital twin: A matheuristics approach. Journal of Manufacturing Systems, 68, 443-454. [pdf]
  13. Song, Y., Ou, J., Wu, J., Wu, Y., Xing, L., & Chen, Y. (2023). A cluster-based genetic optimization method for satellite range scheduling system. Swarm and Evolutionary Computation, 101316. [pdf]
  14. Song, Y., Wei, L., Yang, Q., Wu, J., Xing, L., & Chen, Y. (2023). RL-GA: A reinforcement learning-based genetic algorithm for electromagnetic detection satellite scheduling problem. Swarm and Evolutionary Computation, 101236. [pdf]
  15. Wu, J., Yao, F., Song, Y., He, L., Lu, F., Du, Y., ... & Ou, J. (2023). Frequent Pattern-Based Parallel Search Approach for Time-Dependent Agile Earth Observation Satellite Scheduling. Information Sciences. [pdf]
  16. Ou, J., Xing, L., Yao, F., Li, M., Lv, J., He, Y., Song, Y., ... & Zhang, G. (2023). Deep reinforcement learning method for satellite range scheduling problem. Swarm and Evolutionary Computation, 101233. [pdf]
  17. Yang, Q., Gao, Y., & Song, Y. (2023). A Tent Lévy Flying Sparrow Search Algorithm for Wrapper-Based Feature Selection: A COVID-19 Case Study. Symmetry, 15(2), 316.
  18. Song, Y., Xing, L., & Chen, Y. (2022). Two-stage hybrid planning method for multi-satellite joint observation planning problem considering task splitting. Computers & Industrial Engineering, 108795.
  19. Song, Y., Song, B., Xing, L., Jia, Y., & Chen Y. (2022). Improved artificial bee colony algorithm for satellite-ground cooperative observation planning problem. Control and Decision, 37(3), 555-564.
  20. Jiang, X., Song, Y. (Co-first author), & Xing, L. (2022). Dual-population Artificial Bee Colony Algorithm for Joint Observation Satellites Mission Planning Problem. IEEE Access.
  21. Wei, L., Xing, L., Wan, Q., Song, Y., & Chen, Y. (2021). A Multi-objective Memetic Approach for Time-dependent Agile Earth Observation Satellite Scheduling Problem. Computers & Industrial Engineering, 159, 107530.
  22. Chen, M., Wen, J., Song, Y. J., Xing, L. N., & Chen, Y. W. (2021). A population perturbation and elimination strategy based genetic algorithm for multi-satellite TT&C scheduling problem. Swarm and Evolutionary Computation, 65, 100912.
  23. Song, Y., Xing, L., Wang, M., Yi, Y., Xiang, W., & Zhang, Z. (2020). A knowledge-based evolutionary algorithm for relay satellite system mission scheduling problem. Computers & Industrial Engineering, 150, 106830.
  24. Song, Y. J., Zhou, Z. Y., Zhang, Z. S., Yao, F., & Chen, Y. W. (2020). A framework involving MEC: imaging satellites mission planning. Neural Computing and Applications, 32(19), 15329-15340.
  25. Song, Y. J., Ma, X., Li, X. J., Xing, L. N., & Wang, P. (2019). Learning-guided nondominated sorting genetic algorithm II for multi-objective satellite range scheduling problem. Swarm and Evolutionary Computation, 49, 194-205.
  26. Song, Y. J., Zhang, Z. S., Sun, K., Yao, F., & Chen, Y. W. (2019). A heuristic genetic algorithm for regional targets’ small satellite image downlink scheduling problem. International Journal of Aerospace Engineering, 2019.
  27. Song, Y. J., Wang, P., Zhang, Z. S., Xing, L. N., & Chen, Y. W. (2019). An Improved Genetic Algorithm for Multi-Satellite Mission Planning Problem. Control Theory & Applications, 36(9), 1391-1397.
  28. Song, Y. J., Zhang, Z. S., Song, B. Y., & Chen, Y. W. (2019). Improved genetic algorithm with local search for satellite range scheduling system and its application in environmental monitoring. Sustainable Computing: Informatics and Systems, 21, 19-27.
  29. Yao, F., Song, Y. J.*, Zhang, Z. S., Xing, L. N., Ma, X., & Li, X. J. (2019). Multi-mobile robots and multi-trips feeding scheduling problem in smart manufacturing system: An improved hybrid genetic algorithm. International Journal of Advanced Robotic Systems, 16(4), 1729881419868126.
  30. Wang, Q., Luo, H., Xiong, J., Song, Y.*, & Zhang, Z. (2019). Evolutionary algorithm for aerospace shell product digital production line scheduling problem. Symmetry, 11(7), 849.
  31. Song, Y. J., Song, B. Y., Zhang, Z. S., & Chen, Y. W. (2018). The satellite downlink replanning problem: A BP neural network and hybrid algorithm approach for IoT Internet connection. IEEE Access, 6, 39797-39806.
  32. Song, Y., Huang, D., Zhou, Z., & Chen, Y. (2018). An emergency task autonomous planning method of agile imaging satellite. EURASIP Journal on Image and Video Processing, 2018(1), 1-11.

Book Chapters

  1. Bees Algorithm with Adaptive Operator Selection Mechanism for Generalised Multi-dimensional Multi-choice Knapsack Problem (Forthcoming)
  2. A Tabu-Based Bees Algorithm for Unmanned Aerial Vehicles in Maritime Search and Rescue Path Planning (Forthcoming)
  3. A Knowledge Transfer-based Bees Algorithm for Expert Team Formation Problem in Internet Company (Forthcoming)
  4. Song, Y., Xing, L., Chen, Y. (2022). Application of the Dual-population Bees Algorithm in a Parallel Machine Scheduling Problem with a Time Window, Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach. Editor: Duc Truong Pham, Natalia Hartono

Conference Papers

  1. Huang, Y., Luo, A., Zhang, M., Bai, L., Song, Y., & Li, J. (2023, April). Task Location Distribution Based Genetic Algorithm for UAV Mobile Crowd Sensing. In Bio-Inspired Computing: Theories and Applications: 17th International Conference, BIC-TA 2022, Wuhan, China, December 16–18, 2022, Revised Selected Papers (pp. 165-178). Singapore: Springer Nature Singapore.
  2. Song, Y. J., Ou, J. W., Pham, D. T., Li, J. T., Huang, J. B., & Xing, L. N. (2023, April). A Reinforcement-Learning-Driven Bees Algorithm for Large-Scale Earth Observation Satellite Scheduling. In Bio-Inspired Computing: Theories and Applications: 17th International Conference, BIC-TA 2022, Wuhan, China, December 16–18, 2022, Revised Selected Papers (pp. 81-91). Singapore: Springer Nature Singapore.
  3. Wang, H., Li, J., Song, Y., Huang, J., Li, J., & Chen, Y. (2022, December). An Improved Genetic Algorithm for Team Formation Problem. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 774-781). IEEE.
  4. Huang, Y., Luo, A., Zhang, M., Zhang, X., Lin, M., & Song, Y. (2022, August). A Novel Mission Planning Model and Method for Combat system-of-systems Architecture Design. In 2022 8th International Conference on Big Data and Information Analytics (BigDIA) (pp. 239-245). IEEE.
  5. Song, Y., Wei, L., Xing, L., Fang, Y., Zhang, Z., & Chen, Y. (2021). Solving Satellite Range Scheduling Problem with Learning-Based Artificial Bee Colony Algorithm. BIC-TA.
  6. Wei, L.,Song, Y., Xing, L., Chen, M., & Chen, Y. (2021). A Hybrid Multi-objective Coevolutionary Approach for the Multi-user Agile Earth Observation Satellite Scheduling Problem. BIC-TA.
  7. Song, Y., Song, B., Huang, Y., Xing, L., & Chen, Y. (2021, December). Solving Large-scale Relay Satellite Scheduling Problem with A Dynamic Population Firework Algorithm: A Case Study. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-7). IEEE.
  8. Chen, Y., Song, Y. (Co-first Author), Du, Y., Wang, M., Zong, R., & Gong, C. (2020, August). A knowledge-based scheduling method for multi-satellite range system. In International Conference on Knowledge Science, Engineering and Management (pp. 388-396). Springer, Cham.
  9. Chen, M., Wen, J., Pi, B. J., Wang, H., Song, Y. J., & Xing, L. N. (2019, November). A Novel Genetic Algorithm with Population Perturbation and Elimination for Multi-satellite TT&C Scheduling Problem. In International Conference on Bio-Inspired Computing: Theories and Applications (pp. 558-568). Springer, Singapore.
  10. Ma, X., Li, X., Song, Y., Zheng, X., Zhang, Z., & He, R. (2019, July). A bp neural network for identifying corporate financial fraud. In 2019 IEEE International Conference on Intelligence and Security Informatics (ISI) (pp. 191-193). IEEE.
  11. Ma, X., Zhang, Y., Song, Y. J., Zhang, Z. S., Yao, F., & Han, X. D. (2019, March). A Fast and Effective Solution Algorithm for Satellite Measurement and Control Scheduling Problem. In Proceedings of the International Conference on Industrial Control Network and System Engineering Research (pp. 14-17).
  12. Song, Y. J., Ma, X., Zhang, Z. S., Xing, L. N., & Chen, Y. W. (2018, November). A hybrid dynamic population genetic algorithm for multi-satellite and multi-station mission planning system. In International Conference on Bio-Inspired Computing: Theories and Applications (pp. 444-453). Springer, Singapore.

Patents

  1. Chinese Patent. Reinforcement Learning-based Two-layer Energy Storage Scheduling Model and Adaptive Optimization of Energy Storage Technology.
  2. Chinese Patent. UAV Maritime Search and Rescue Path Planning Using A Tuba-based Bees Algorithm.
  3. Chinese Patent. Cluster-based Satellite Measurement and Control Scheduling Method and System, Patent Pending Number: 2022104076790.
  4. Chinese Patent. Multi-satellite Joint Planning Method and System Considering Task Splitting, Patent Pending Number: 2022103947224.
  5. Chinese Patent. Imaging Satellite Autonomous Mission Planning Method based on Machine Learning, Patent Pending Number: 201910034280.0
  6. Chinese Patent. A Reinforcement Learning based Evolution Method, System and Device for Satellite Mission Planning, Patent Pending Number: 2022104852062
  7. Chinese Patent. Online scheduling method for dynamically arriving tasks, Patent Pending Number: 2020101029515
  8. Chinese Software Copyright. Navigation and message return business planning software, Copyright Registration Number: 2019SR0324482.

Working Papers

  1. A Reinforcement learning-based two-layer Adaptive Optimization Method for User-side Energy Storage Scheduling Problem
  2. Multi-Objective Flexible Job Shop Scheduling via Preference-Conditioned Graph Reinforcement Learning
  3. Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities [pdf]
  4. Identifying and prioritizing key factors for smart aviation development using the fuzzy best-worst method: A case from China
  5. A Reinforcement Learning-based Memetic Algorithm for Energy-Efficient Satellite Range Scheduling Problem
  6. Container Shipping Contract Design under Financial Constraints and Default Risks
  7. A Reinforcement Learning-assisted Genetic Programming Algorithm for Team Formation Problem Considering Person-Job Matching [pdf]
  8. Dynamic Multi-Objective Optimization Algorithm Guided by Recurrent Neural Network