Papers

Journal papers

  1. Jingda Deng and Qingfu Zhang, “Combining simple and adaptive Monte Carlo methods for approximating hypervolume,” IEEE Transactions on Evolutionary Computation, vol. 24, no. 5, pp. 896-907, 2020
  2. Jingda Deng and Qingfu Zhang, “Approximating hypervolume and hypervolume contributions using polar coordinate,” IEEE Transactions on Evolutionary Computation, vol. 23, no. 5, pp. 913-918, 2019
  3. Hui Li, Jingda Deng, Qingfu Zhang, and Jianyong Sun, “Adaptive epsilon dominance in decomposition-based multiobjective evolutionary algorithm,” Swarm and Evolutionary Computation, vol. 45, pp. 52-67, 2019
  4. Hui Li, Qingfu Zhang, Jingda Deng, and Zongben Xu, “A preference-based multiobjective evolutionary approach for sparse optimization, ” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 5, pp. 1716-1731, 2018
  5. Hui Li, Qingfu Zhang, and Jingda Deng, “Biased multiobjective optimization and decomposition algorithm,” IEEE Transactions on Cybernetics, vol 47, no. 1, pp. 52-66, 2017

Conference papers

  1. Zhenhua Li, Jingda Deng, Weifeng Gao, Qingfu Zhang, and Hai-Lin Liu, “An efficient elitist covariance matrix adaptation for continuous local search in high dimension,” in 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2019, pp. 936-943.

  2. Jingda Deng, Qingfu Zhang, and Hui Li, “On the use of dynamic reference points in HypE,” in the 11th Asia-Pacific Conference on Simulated Evolution and Learning (SEAL). Springer, Cham, 2017, pp. 122-133.

  3. Hui Li, Yuanyuan Fan, Qingfu Zhang, Zongben Xu, and Jingda Deng, “A multi-phase multiobjective approach based on decomposition for sparse reconstruction,” in 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016, pp. 601-608.

  4. Hui Li, Min Ding, Jingda Deng, and Qingfu Zhang, “On the use of random weights in MOEA/D,” in 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015, pp. 978-985.

  5. Hui Li, Qingfu Zhang, and Jingda Deng, “Multiobjective test problems with complicated Pareto fronts: Difficulties in degeneracy,” in 2014 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2014, pp. 2156-2163.