| Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship R Yan, S Wang, Y Du Transportation Research Part E: Logistics and Transportation Review 138, 101930, 2020 | 127 | 2020 |
| Route and speed optimization for liner ships under emission control policies L Zhen, Z Hu, R Yan, D Zhuge, S Wang Transportation Research Part C: Emerging Technologies 110, 330-345, 2020 | 120 | 2020 |
| Development of a non-parametric classifier: Effective identification, algorithm, and applications in port state control for maritime transportation S Wang, R Yan, X Qu Transportation Research Part B: Methodological 128, 129-157, 2019 | 108 | 2019 |
| Data analytics for fuel consumption management in maritime transportation: Status and perspectives R Yan, S Wang, HN Psaraftis Transportation Research Part E: Logistics and Transportation Review 155, 102489, 2021 | 98 | 2021 |
| Emerging approaches applied to maritime transport research: Past and future R Yan, S Wang, L Zhen, G Laporte Communications in Transportation Research 1, 100011, 2021 | 93 | 2021 |
| An artificial intelligence model considering data imbalance for ship selection in port state control based on detention probabilities R Yan, S Wang, C Peng Journal of Computational Science 48, 101257, 2021 | 71 | 2021 |
| Operation management of green ports and shipping networks: overview and research opportunities L Zhen, D Zhuge, L Murong, R Yan, S Wang Frontiers of Engineering Management 6 (2), 152-162, 2019 | 64 | 2019 |
| A semi-“smart predict then optimize”(semi-SPO) method for efficient ship inspection R Yan, S Wang, K Fagerholt Transportation Research Part B: Methodological 142, 100-125, 2020 | 63 | 2020 |
| Shipping domain knowledge informed prediction and optimization in port state control R Yan, S Wang, J Cao, D Sun Transportation Research Part B: Methodological 149, 52-78, 2021 | 55 | 2021 |
| Implications of the EU’s inclusion of maritime transport in the emissions trading system for shipping companies S Wang, L Zhen, HN Psaraftis, R Yan Engineering 7 (5), 554-557, 2021 | 54 | 2021 |
| Quantitative analysis of the impact of COVID-19 on ship visiting behaviors to ports-A framework and a case study X Wang, Z Liu, R Yan, H Wang, M Zhang Ocean & coastal management 230, 106377, 2022 | 46 | 2022 |
| Integrating prediction with optimization: Models and applications in transportation management R Yan, S Wang Multimodal Transportation 1 (3), 100018, 2022 | 45 | 2022 |
| A smart predict-then-optimize method for targeted and cost-effective maritime transportation X Tian, R Yan, Y Liu, S Wang Transportation Research Part B: Methodological 172, 32-52, 2023 | 42 | 2023 |
| Ship selection in port state control: status and perspectives R Yan, S Wang, C Peng Maritime Policy & Management 49 (4), 600-615, 2022 | 40 | 2022 |
| Ship inspection by port state control—review of current research R Yan, S Wang Smart transportation systems 2019, 233-241, 2019 | 40 | 2019 |
| A data mining method to extract traffic network for maritime transport management Z Liu, H Gao, M Zhang, R Yan, J Liu Ocean & Coastal Management 239, 106622, 2023 | 35 | 2023 |
| Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities Y Song, Y Wu, Y Guo, R Yan, PN Suganthan, Y Zhang, W Pedrycz, S Das, ... Swarm and Evolutionary Computation 86, 101517, 2024 | 25 | 2024 |
| “Predict, then optimize” with quantile regression: A global method from predictive to prescriptive analytics and applications to multimodal transportation S Wang, R Yan Multimodal transportation 1 (4), 2022 | 24 | 2022 |
| A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics S Wang, R Yan Cleaner logistics and supply chain 4, 2022 | 24 | 2022 |
| Is port state control influenced by the COVID-19? Evidence from inspection data R Yan, H Mo, X Guo, Y Yang, S Wang Transport Policy 123, 82-103, 2022 | 22 | 2022 |
Shuaian (Hans) WangThe Hong Kong Polytechnic University在 polyu.edu.hk 的电子邮件经过验证
