Peng Yang (杨鹏)


Curriculum Vitae


Office: Room 913, Nanshan ipark A7 building, Nanshan district, Shenzhen, China.

Research Interest

Evolutionary Policy Optimization, Interactive Evolutionary Computation, and Distributed Evolutionary Computation.

Educational Experience

Research Experience


Referred Journal Publications

  1. 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, in press.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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
  8. 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

  1. 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.
  2. Yunwen Lei, Peng Yang, and Ke Tang. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.


Professonal Services

Special Session

Invited Talks

Journal Reviewer

Conference PC member


Master Students

Undergraduate Students

The End