- Xiuli Wu, Pietro Consoli, Leandro Minku, Gabriela Ochoa, Xin Yao. An Evolutionary Hyper-heuristic for the Software Project Scheduling Problem [C].14th International Conference on Parallel Problem Solving from Nature, PPSN2016, Edingburg,UK,2016.09.17-21.
- Wu Xiuli, Gao Dongliang. A study on greedy search to improve simulated annealing for large-scale traveling salesman problem [C]. 8th International Conference on Swarm Intelligence, ICSI 2017, Fukuoka, Japan,2017,07, 27 -08,01.
- Xiuli Wu，Shaomin Wu. An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem[J]. Journal of Intelligent Manufacturing. 2017,28(6): 1441–1457.
- Wu Xiuli, Xiao Xiao, Zhang Linjuan. Optimizing the three-stage operating room scheduling problem with RVNS-GA [C]. 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018,729-734.
- Wu Xiuli, Li Jing. Discrete harmony search algorithm for flexible job-shop scheduling problems [C]. Communications in Computer and Information Science. 2018,952:31-41.
- Wu Xiuli; Liu Xiajing. An Improved Differential Evolution Algorithm for Solving a Distributed Flexible Job Shop Scheduling Problem [C]. 2018 IEEE 14th International Conference on Automation Science and Engineering, Tech Univ Munich, Munich, Germany.968-973.
- Wu Xiuli, Shen Xianli, Cui Qi. Multi-Objective Flexible Flow Shop Scheduling Problem Considering Variable Processing Time due to Renewable Energy[J]. Sustainability, 2018, 10(3):841.
- Wu Xiuli，Sun Yangjun. A green scheduling algorithm for flexible job shop with energy-saving measures [J]. Journal of Cleaner Production. 2018,172:3249-3264.
- Xiuli Wu, Jing Li, Lin Sun. Hybrid flow shop scheduling problem in ubiquitous manufacturing environment [J]. IET Collaborative Intelligent Manufacturing, 2019,1(2):56-66.
- Wu Xiuli, Shen Xianli, Zhang Linjuan. Solving the planning and scheduling problem simultaneously in a hospital with a bi-layer discrete particle swarm optimization [J]. Mathematical Biosciences and Engineering, 2019, 831-861.