学术论文 | [1] Lin Shi, Z. H. Zhan, D. Liang, and J. Zhang, “Memory-based ant colony system approach for multi-source data associated dynamic electric vehicle dispatch optimization,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 10, pp. 17491-17505, Oct. 2022. [2] Z. H. Zhan, Lin Shi, K. C. Tan, and J. Zhang, “A survey on evolutionary computation for complex continuous optimization,” Artificial Intelligence Review, vol. 55, pp. 59–110, 2022. (学生一作，ESI高被引论文) [3] L. J. Wu, Lin Shi, Z. H. Zhan, K. K. Lai, and J. Zhang, “A buffer-based ant colony system approach for dynamic cold chain logistics scheduling,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6, no. 6, pp. 1438-1452, Dec. 2022. (共同一作) [4] J. Hong, Lin Shi, K. J. Du, C. H. Chen, H. Wang, J. Zhang, and Z. H. Zhan, “A multi-population genetic algorithm for multiobjective recommendation system,” in Proceedings of IEEE Symposium Series on Computational Intelligence, 2023, pp.998-1003. [5] Xu Li, Lin Shi, Jian-Yu Li, Jing Xu, and Zhi-Hui Zhan, “Pheromone matrix eigenvalue-based convergence assessment indicator for ant colony optimization,” International Conference on Machine Intelligence Theory and Applications, Melbourne, Australia, 2024. (通讯作者) |
