Peng Yang (杨鹏)



Research Interest

My research interests focus on Real-time Evolutionary Computation System and its applications in Finance.

Educational Experience

Research Experience


Referred Journal Publications

  1. Jinghui Zhong, Tiantian Cheng,Wei-Li Liu, Peng Yang, Ying Lin, and Jun Zhang. An Evolutionary Guardrail Layout Design Framework for Crowd Control in Subway Station. IEEE Transactions on Computational Social Systems, 2022, doi:10.1109/TCSS.2022.3140310.
  2. 刘晟材, 杨鹏, 唐珂. 近似最优并行算法组智能汇聚构造. 中国科学:技术科学, 2021, 接收.
  3. Wenxing Lan, Ziyuan Ye, Peijun Ruan, Jialin Liu, Peng Yang, and Xin Yao. Region-focused Memetic Algorithms with Smart Initialisation for Real-world Large-scaleWaste Collection Problems. IEEE Transactions on Evolutionary Computation, 2021, doi:10.1109/TEVC.2021.3123960.
  4. Peng Yang, Hu Zhang, Yanglong Yu, Mingjia Li, and Ke Tang. Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search. Swarm and Evolutionary Computation. Vol.68, 100974, 2021.
  5. Shengcai Liu, Peng Yang, Ke Tang, and Xin Yao. Few-shots Parallel Algorithm Portfolio Construction via Co-evolution. IEEE Transactions on Evolutionary Computation. Vol. 25, Issue. 3, pp. 595 - 607, 2021.
  6. Peng Yang, Qi Yang, Ke Tang, and Xin Yao. Parallel Exploration via Negatively Correlated Search. Frontiers of Computer Science. Vol.15, Issue 5, pp.155333, 2021.
  7. Wenjing Hong, Peng Yang, and Ke Tang. Evolutionary Computation for Large-Scale Multi-Objective Optimization: A Decade of Progresses. International Journal of Automation and Computing. 18, 155–169, 2021.
  8. Minshi Chen, Jianxun Chen, Peng Yang, Shengcai Liu, and Ke Tang. A heuristic repair method for dial-a-ride problem in intracity logistic based on neighborhood shrinking. Multimedia Tools and Applications, 2020, DOI: 10.1007/s11042-020-08894-7.
  9. Dongbin Jiao, Peng Yang, Liqun Fu, Liangjun Ke, and Ke Tang. Optimal Energy-Delay Scheduling for Energy Harvesting WSNs with Interference Channel via Negatively Correlated Search. IEEE Internet of Things Journal, Vol. 7, Issue 3, pp. 1690-1703, 2020.
  10. Peng Yang, Ke Tang and Xin Yao. A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization. IEEE Access, vol. 7, pp. 163105-163118, 2019.
  11. Peng Yang, Ke Tang and Xin Yao. Turning High-dimensional Optimization into Computationally Expensive Optimization. IEEE Transactions on Evolutionary Computation, Vol. 22, Issue 1, pp. 143-156, 2018.
  12. Jinhong Zhong, Peng Yang, Ke Tang. A Quality-Sensitive Method for Learning from Crowds. IEEE Transactions on Knowledge and Data Engineering, Vol. 29, Issue 12, pp. 2643-2654, 2017.
  13. Peng Yang, Ke Tang and Xiaofen Lu. Improving Estimation of Distribution Algorithm on Multi-modal Problems by Detecting Promising Areas. IEEE Transactions on Cybernetics, Vol. 45, Issue 8, pp. 1438-1449, 2015.
  14. Peng Yang, Ke Tang, Jose A. Lozano and Xianbin Cao. Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints. IEEE Transactions on Robotics, Vol. 31, Issue 5, pp. 1130-1146, 2015
  15. Ke Tang, Peng Yang and Xin Yao. Negatively Correlated Search. IEEE Journal on Selected Areas in Communications, Vol. 34, Issue 3, pp. 1-9, March 2016.

Referred Conference Publications (^ for Correspongding Author)

  1. Zhibin Miao, Jinghui Zhong, and Peng Yang. Implicit Neural Network for Implicit Data Regression Problems. In Proceedings of the 28th International Conference on Neural Information Processing (ICONIP'2021), pp.187-195, Sanur, Bali, Indonesia; 12/2021.
  2. Qi Yang, Peng Yang, and Ke Tang. Parallel Random Embedding with Negatively Correlated Search. In: Proceedings of the 12th International Conference on Swarm Intelligence (ICSI 2021), Qingdao, China; 2021/7.
  3. Wenjing Hong, Peng Yang, Yiwen Wang, and Ke Tang. Multi-Objective Magnitude-Based Pruning for Latency-Aware Deep Neural Network Compression. In: Proceedings of the 2020 International Conference on Parallel Problem Solving from Nature (PPSN XVI), Leiden, Netherlands; 09/2020.
  4. Yunwen Lei, Peng Yang, Ke Tang, and Ding-Xuan Zhou. Optimal Stochastic and Online Learning with Individual Iterates. In: Proceedings of Conference and Workshop on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada; 12/2019.
  5. Er Zhuo, Yunjie Deng, Zhewei Su, Peng Yang, Bo Yuan, and Xin Yao. An Experimental Study of Large-scale Capacitated Vehicle Routing Problems. In: Proceedings of the 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019), Wellington, New Zealand; 06/2019.
  6. Dongbing Jiao, Peng Yang, Liqun Fu, Liangjun Ke, and Ke Tang. Optimal Energy-Delay Scheduling for Energy Harvesting WSNs via Negatively Correlated Search. In: Proceedings of the 2019 International Conference on Communications (ICC 2019), Shanghai, China; 07/2019.
  7. Dongjun Qian, Peng Yang^, and Ke Tang. A Fast Heuristic Path Computation Algorithm for Batch Bandwidth Constrained Routing Problem in SDN. In: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI2018),Nanjing, China; 08/2018, Springer. To appear.
  8. Peng Yang, Guanzhou Lu, Ke Tang and Xin Yao. A Multi-Modal Optimization Approach to Single Path Planning for Unmanned Aerial Vehicle. In: Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC2016), pp.1735-1742, Vancouver, Canada; 07/2016, IEEE.
  9. Peng Yang, Ke Tang and Jose A. Lozano. Estimation of Distribution Algorithms based Unmanned Aerial Vehicle Path Planner Using a New Coordinate System. In: Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014), pp.1469-1476, Beijing, China; 07/2014, IEEE.
  10. Peng Yang, Ke Tang, Lingxi Li and Kai Qin. Evolutionary Robust Optimization with Multiple Solutions. In: Proceedings of The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Nov., 2015, Singapore; pp.611-625, Springer.
  11. Wenjing Hong, Guanzhou Lu, Peng Yang, Yong Wang and Ke Tang. A New Evolutionary Multi- objective Algorithm for Convex Hull Maximization. In: Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC2015), pp.931-938, Sendai, Japan; 05/2015, IEEE.



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The End