Fangfang Zhang

Fangfang Zhang

Lecturer, Victoria University of Wellington

Publications

Authored Books

  1. Fangfang Zhang, Su Nguyen, Yi Mei, and Mengjie Zhang. “Genetic Programming for Production Scheduling: An Evolutionary Learning Approach”. Springer Book Series on Machine Learning: Foundations, Methodologies, and Applications，2021. DOI: 10.1007/978-981-16-4859-5, eBook ISBN 978-981-16-4859-5 (XXXIII+338 pages, the first book on hyper-heuristic for production scheduling) [pdf]

Refereed Journal Articles

  1. Zhixing Huang, Yi Mei, Fangfang Zhang*, Mengjie Zhang, and Wolfgang Banzhaf. "Fitness Landscape Optimization Makes Stochastic Symbolic Search By Genetic Programming Easier". IEEE Transactions on Evolutionary Computation, 2024. [pdf]
  2. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Learn to Optimise for Job Shop Scheduling: A Survey with Comparison between Genetic Programming and Reinforcement Learning". Artificial Intelligence Review, 2024. DOI: DOI : 10.1007/s10462-024-11059-9 [pdf]
  3. Kun Huang, Fang-Lue Zhang, Fangfang Zhang, Yu-Kun Lai, Paul Rosin, and Neil Dodgson. "Multi-task Geometric Estimation of Depth and Surface Normal from Monocular 360° Images". Computational Visual Media Journal, 2024.
  4. Yuye Zhang, Fangfang Zhang*, Paula Casanovas, Bing Xue, Mengjie Zhang, and Jane E. Symonds. "A Study of Feature Importance for King Salmon Health Classification with Feature Selection". Intelligent Marine Technology and Systems, 2024. DOI: 10.1007/s44295-024-00046-z [pdf]
  5. Fangfang Zhang, Gaofeng Shi, Yi Mei, and Mengjie Zhang. "Multi-objective Dynamic Flexible Job Shop Scheduling with Biased Objectives via Multitask Genetic Programming". IEEE Transactions on Artificial Intelligence, 2024. DOI: 10.1109/TAI.2024.3456086 [pdf]
  6. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Niching Genetic Programming to Learn Actions for Deep Reinforcement Learning in Dynamic Flexible Scheduling". IEEE Transactions on Evolutionary Computation, 2024. DOI: 10.1109/TEVC.2024.3395699 [pdf]
  7. Zaixing Sun, Yi Mei, Fangfang Zhang, Hejiao Huang, Chonglin Gu, and Mengjie Zhang. "Multi-Tree Genetic Programming Hyper-Heuristic for Dynamic Flexible Workflow Scheduling in Multi-Clouds". IEEE Transactions on Services Computing, 2024. DOI: 10.1109/TSC.2024.3394691 [pdf]
  8. Fangfang Zhang, Yuye Zhang, Paula Casanovas, Jessica Schattschneider, Seumas P. Walker, Bing Xue, Mengjie Zhang, and Jane E. Symonds. "Health Prediction for King Salmon via Evolutionary Machine Learning with Genetic Programming". Journal of the Royal Society of New Zealand, vol. 55, no. 1, pp. 166-191, 2024. DOI: 10.1080/03036758.2024.2329228 [pdf]
  9. Yun Liu, Fangfang Zhang, Yanan Sun, and Mengjie Zhang. "Evolutionary Trainer-based Deep Q-Network for Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, 2024. DOI: 10.1109/TEVC.2024.3367181 [pdf]
  10. Zhixing Huang, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Toward Evolving Dispatching Rules with Flow Control Operations by Grammar-guided Linear Genetic Programming". IEEE Transactions on Evolutionary Computation, 2024. DOI: 10.1109/TEVC.2024.3353207 [pdf]
  11. Zhixing Huang, Yi Mei, Fangfang Zhang*, Mengjie Zhang, and Wolfgang Banzhaf. "Bridging Directed Acyclic Graphs to Linear Representations in Linear Genetic Programming". Genetic Programming and Evolvable Machines, 2024. DOI: 10.1007/s10710-023-09478-8 [pdf]
  12. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming and Reinforcement Learning on Learning Heuristics for Dynamic Scheduling: A Preliminary Comparison". IEEE Computational Intelligence Magazine, vol. 19, no. 2, pp. 18-33, 2024. DOI: 10.1109/MCI.2024.3363970 [pdf] (Research Frontier)
  13. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 28, no. 1, pp. 147-167, 2023. DOI: 10.1109/TEVC.2023.3255246 [pdf] (Selected as a Popular Paper)
  14. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming for Dynamic Flexible Job Shop Scheduling: Evolution with Single Individuals and Ensembles". IEEE Transactions on Evolutionary Computation, vol. 28, no. 6, pp. 1761-1775, 2024. DOI: 10.1109/TEVC.2023.3334626 [pdf]
  15. Zhixing Huang, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Multitask Linear Genetic Programming with Shared Individuals and its Application to Dynamic Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 28, no. 6, pp. 1546-1560, 2024. DOI: 10.1109/TEVC.2023.3263871 [pdf]
  16. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming with Lexicase Selection for Large-scale Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 28, no. 5, pp. 1235-1249, 2024. DOI: 10.1109/TEVC.2023.3244607 [pdf]
  17. Meng Xu, Yi Mei, Shiqiang Zhu, Beibei Zhang, Tian Xiang, Fangfang Zhang, and Mengjie Zhang. "Genetic Programming for Dynamic Workflow Scheduling in Fog Computing". IEEE Transactions on Services Computing, 2023. DOI: 10.1109/TSC.2023.3249160 [pdf]
  18. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Cybernetics, vol. 53, no. 7, pp. 4473-4486, 2022. DOI: 10.1109/TCYB.2022.3196887 [pdf]
  19. Fangfang Zhang, Yi Mei, Su Nguyen, Kay Chen Tan, and Mengjie Zhang. "Task Relatedness Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 27, no. 6, pp. 1705-1719, 2022. DOI: 10.1109/TEVC.2022.3199783 [pdf] (Selected as a Popular Paper)
  20. Fangfang Zhang, Yi Mei, Su Nguyen, Kay Chen Tan, and Mengjie Zhang. "Instance Rotation Based Surrogate in Genetic Programming with Brood Recombination for Dynamic Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 27, no. 5, pp. 1192-1206, 2022. Doi: 10.1109/TEVC.2022.3180693 [pdf]
  21. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Collaborative Multi-fidelity Based Surrogate Models for Genetic Programming in Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Cybernetics, vol. 52, no. 8, pp. 8142-8156, 2022. [DOI][pdf]
  22. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Correlation Coefficient Based Recombinative Guidance for Genetic Programming Hyper-heuristics in Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 25, no. 3, pp. 552-566, 2021. [DOI][pdf] (Selected as a Popular Paper)
  23. Fangfang Zhang, Yi Mei, Su Nguyen, Kay Chen Tan, and Mengjie Zhang. "Surrogate-Assisted Evolutionary Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Evolutionary Computation, vol. 25, no. 4, pp. 651-665, 2021. [DOI][pdf] (Selected as a Popular Paper)
  24. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Evolving Scheduling Heuristics via Genetic Programming with Feature Selection in Dynamic Flexible Job Shop Scheduling". IEEE Transactions on Cybernetics, vol. 51, no. 4, pp. 1797-1811, 2021. [DOI][pdf] (Selected as a Popular Paper)
  25. Fangfang Zhang, Yi Mei, Su Nguyen, Kay Chen Tan, and Mengjie Zhang. "Multitask Genetic Programming-Based Generative Hyper-heuristics: A Case Study in Dynamic Scheduling". IEEE Transactions on Cybernetics, vol. 52, no. 10, pp. 10515-10528, 2022. Doi: 10.1109/TCYB.2021.3065340. [DOI][pdf]
  26. Qingyu Zhang, Mei Cao, Fangfang Zhang, Jing Liu, and Xin Li. "Effects of Corporate Social Responsibility on Customer Satisfaction and Organizational Attractiveness: A Signaling Perspective". Business Ethics: A European Review, vol. 29, no. 1, pp. 20-34, 2020. [DOI][pdf]
  27. Fangfang Zhang, Ben Niu, Li Li, Lang Wu. “Intelligent Optimization for Truck Dispatch with the Yard Storage Location Varying Factor”. Chinese journal of Management Science, 2016, pp. 8. (In Chinese) [DOI][pdf]
  28. Li Li, Fangfang Zhang, Yuan Liu, and Wenjie Yi. “A Study on the Key Factors Affecting MOOC Learning Quality-Based on Learner Behavior Perspective”. Journal of Industrial and Information Education, 2016, 2016(8): 42-52. (In Chinese). [DOI][pdf]
  29. Ben Niu, Ying Bi, Fangfang Zhang, Jing Liu. “Optimization of Production Scheduling in Injection Workshop with Machine and Mold Consideration”. Chinese journal of Management Science, 2015, pp. 7 (In Chinese) [DOI][pdf]

Conference Papers

  1. Ruiqi Chen, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Neural Network Surrogate based on Binary Classification for Assisting Genetic Programming in Searching Scheduling Heuristic". in Proceedings of the Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2024, pp. 309–321. [pdf]
  2. Zaixing Sun, Fangfang Zhang, Yi Mei, Hejiao Huang, Chonglin Gu, Bin Qian, and Mengjie Zhang. "Evolving Scheduling Heuristics for Energy-Efficient Dynamic Workflow Scheduling in Cloud via Genetic Programming Hyper-heuristics". International Conference on Intelligent Computing, 2024, pp. 169–182. [pdf]
  3. Luyao Zhu, Fangfang Zhang, Mengyuan Feng, Ke Chen, Xiaodong Zhu, and Mengjie Zhang. "Crossover Operators Between Multiple Scheduling Heuristics with Genetic Programming for Dynamic Flexible Job Shop Scheduling", in Proceedings of the Congress on Evolutionary Computation, IEEE, 2024, DOI: 10.1109/CEC60901.2024.10612212.[pdf]
  4. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling", in Proceedings of the Australasian Joint Conference on Artificial Intelligence, IEEE, 2023, pp. 403-415. (Best Poster Runner-up Award) [pdf]
  5. Gaofeng Shi, Fangfang Zhang*, and Yi Mei. "Interpretability-Aware Multi-Objective Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling", in Proceedings of the Congress on Evolutionary Computation, IEEE, 2023, DOI: 10.1109/CEC53210.2023.10253970.
  6. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "An Investigation of Terminal Settings on Multitask Multi-objective Dynamic Flexible Job Shop Scheduling with Genetic Programming", in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2023, pp. 259-262.
  7. Jordan MacLachlan, Yi Mei, Fangfang Zhang, and Mengjie Zhang. "Learning Emergency Medical Dispatch Policies Via Genetic Programming", in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2023, pp. 1409–1417.
  8. Zhixing Huang, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Grammar-guided Linear Genetic Programming for Dynamic Job Shop Scheduling", in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2023, pp. 1137–1145. (Best Paper Award)
  9. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Multi-Objective Genetic Programming based on Decomposition on Evolving Scheduling Heuristics for Dynamic Scheduling", in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2023, pp. 427–430.
  10. Luyao Zhu, Fangfang Zhang, Ke Chen, Xiaodong Zhu, and Mengjie Zhang. "Sample-Aware Surrogate-Assisted Genetic Programming for Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling", in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2023, pp. 384–392.
  11. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Phenotype Based Surrogate-Assisted Multi-objective Genetic Programming with Brood Recombination for Dynamic Flexible Job Shop Scheduling", in Proceedings of the IEEE Symposium Series On Computational Intelligence, Springer, 2022, pp. 1218-1225.
  12. Zhixing Huang, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "A Further Investigation to Improve Linear Genetic Programming in Dynamic Job Shop Scheduling", in Proceedings of the IEEE Symposium Series On Computational Intelligence, Springer, 2022, pp. 496-503.
  13. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Importance-Aware Genetic Programming for Automated Scheduling Heuristics Learning in Dynamic Flexible Job Shop Scheduling". in Proceedings of the Parallel Problem Solving from Nature, Springer, 2022, pp. 48-62. [pdf]
  14. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Learning Strategies on Scheduling Heuristics of Genetic Programming in Dynamic Flexible Job Shop Scheduling". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2022, DOI: 10.1109/CEC55065.2022.9870243. [pdf]
  15. Gaofeng Shi, Fangfang Zhang*, and Yi Mei. "A Novel Fitness Function for Genetic Programming in Dynamic Flexible Job Shop Scheduling". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2022, DOI: 10.1109/CEC55065.2022.9870235. [pdf]
  16. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming with Cluster Selection for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2022, DOI: 10.1109/CEC55065.2022.9870431. [pdf]
  17. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming with Multi-case Fitness for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2022, DOI: 10.1109/CEC55065.2022.9870340. [pdf]
  18. Jordan MacLachlan, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming for Vehicle Subset Selection in Ambulance Dispatching". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2022, DOI: 10.1109/CEC55065.2022.9870323. [pdf]
  19. Zhixing Huang, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Graph-based Linear Genetic Programming: A Case Study of Dynamic Scheduling". in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2022, pp. 955-963. [pdf]
  20. Meng Xu, Yi Mei, Fangfang Zhang*, and Mengjie Zhang. "Genetic Programming with Diverse Partner Selection for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2022, pp. 615-618. [pdf]
  21. Zhixing Huang, Fangfang Zhang*, Yi Mei, and Mengjie Zhang. "An Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop Scheduling". in Proceedings of the European Conference on Genetic Programming, Springer, 2022, pp. 162-178 (Best Paper Award)[pdf]
  22. Meng Xu, Fangfang Zhang*, Yi Mei, and Mengjie Zhang. "Genetic Programming with Archive for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2021, pp. 2117-2124. [DOI][pdf]
  23. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "A Preliminary Approach to Evolutionary Multitasking for Dynamic Flexible Job Shop Scheduling via Genetic Programming". in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2020, pp. 107-108. [DOI][pdf]
  24. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling". in Proceedings of the European Conference on Genetic Programming, Springer, 2020, pp. 262-278. [DOI][pdf]
  25. Fangfang Zhang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling". in Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimisation, Springer, 2020, pp. 214-230. [DOI][pdf]
  26. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "A Two-stage Genetic Programming Hyper-heuristic Approach with Feature Selection for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Genetic and Evolutionary Computation Conference, ACM, 2019, pp. 347-355. [DOI][pdf]
  27. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Can Stochastic Dispatching Rules Evolved by Genetic Programming Hyperheuristics Help in Dynamic Flexible Job Shop Scheduling?". in Proceedings of the Congress on Evolutionary Computation, IEEE, 2019, pp. 41-48. [DOI][pdf]
  28. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Evolving Dispatching Rules for Multi-objective Dynamic Flexible Job Shop Scheduling via Genetic Programming Hyper-heuristics". in Proceedings of the Congress on Evolutionary Computation, 2019, pp. 1343-1350. [DOI][pdf]
  29. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "A New Representation in Genetic Programming for Evolving Dispatching Rules for Dynamic Flexible Job Shop Scheduling". in Proceedings of the European Conference on Evolutionary Computation in Combinatorial Optimization, Springer, 2019, pp. 33-49. [DOI][pdf]
  30. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Australasian Joint Conference on Artificial Intelligence, Springer, 2018, pp. 472-484. (Best Paper Runner-Up Award) [DOI][pdf]
  31. Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Surrogate-Assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling". in Proceedings of the Australasian Joint Conference on Artificial Intelligence, Springer, 2018, pp. 766-772. [DOI][pdf]
  32. Fangfang Zhang, Li Li, Jing Liu, Xianghua Chu. “Artificial Bee Colony Optimization for Yard Truck Scheduling and Storage Allocation Problem”. in Proceedings of the International Conference on Intelligent Computing, Springer, 2016, pp. 908-917. [DOI][pdf]
  33. Li Li, Fangfang Zhang, Cheng Liu, and Ben Niu. “A hybrid Artificial Bee Colony Algorithm with Bacterial Foraging Optimization”. in Proceedings of the Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, IEEE, 2015, pp. 127-132. [DOI][pdf]
  34. Li Li, Fangfang Zhang, Xianghua Chu, Ben Niu. “Modified Brain Storm Optimization Algorithms Based on Topology Structures”. in Proceedings of the International Conference on Swarm Intelligence, Springer, 2016, pp. 408-415. [DOI][pdf]
  35. Ben Niu, Fangfang Zhang, Li Li, Lang Wu. “Particle Swarm Optimization for Yard Truck Scheduling in Container Terminal with a Cooperative Strategy”. in Proceedings of the Asia-Pacific Symposium on Intelligent and Evolutionary Systems, Springer, 2017, pp. 333-346. [DOI][pdf]
  36. Hanyang Luo, Fangfang Zhang, Jing Liu, Xin Li. “Empirical Research on the Effect of Online Product Recommendations on Consumers’ Shopping Efficiency”. in Proceedings of the International Conference on eBusiness, eCommerce, eManagement, eLearning and eGovernance, 2015, pp. 88-92. [DOI][pdf]
  37. Ben Niu, Jing Liu, Fangfang Zhang, Wenjie Yi. “A Cooperative Structure-Redesigned-Based Bacterial Foraging Optimization with Guided and Stochastic Movements”. in Proceedings of the International Conference on Intelligent Computing, Springer, 2016, pp. 918-927. [DOI][pdf]
  38. Lijing Tan, Hong Wang, Fangfang Zhang, Yuanyue Feng. “A Multiobjective Bacterial Optimization Method Based on Comprehensive Learning Strategy for Environmental/Economic Power Dispatch”. in Proceedings of the International Conference on Swarm Intelligence, Springer, 2016, pp. 400-407. [DOI][pdf]
  39. Xin Li, Jing Liu, Fangfang Zhang. “Different Effects of Provider Recommendations and Consumer Reviews on Consumers' Shopping Efficiency for Different Product Types”. in Proceedings of the International Conference on Service Systems and Service Management, Springer, 2016, pp. 1-6. [DOI][pdf]
  40. Xiaobing Gan, Lijiao Liu, Ben Niu, Lijing Tan, Fangfang Zhang, Jing Liu. “SRBFOs for Solving the Heterogeneous Fixed Fleet Vehicle Routing Problem”. in Proceedings of the International Conference on Intelligent Computing, Springer, 2015, pp 725-731. [DOI][pdf]
  41. Fangfang Zhang, Li Li, Jing Liu, Chen Yang. “An Analysis of Factors Affecting the Willingness to Use Credit Card”. in Proceedings of the Chinese Annual Conference of Management, 2015, pp. 7 (In Chinese) [DOI][pdf]

Theses

  1. PhD thesis, Fangfang Zhang. "Genetic Programming Hyper-heuristics for Dynamic Flexible Job Shop Scheduling". 2021, 300 pages, DOI: https://doi.org/10.26686/wgtn.16528677 [pdf]
    2022 SIGEVO Dissertation Award, Honorable Mention
    2025 IEEE CIS Outstanding PhD Dissertation Award
    My PhD proposal is here
  2. Master thesis, Fangfang Zhang. "Optimization Research for Yard Truck Scheduling in Container Terminal". 2017, 56 pages (In Chinese) [DOI][caj]

Patents

  1. Intelligent anti-drowning device, Utility Model Patent, 2018-2028