中文版

https://yiping0liu.github.io/index_cn.html

Homepage (in English)

https://yiping0liu.github.io/

主要研究方向包括但不限于以下：

计算智能的理论与方法：进化计算、机器学习、多目标优化、多模态优化、融合机器学习的进化优化、神经网络架构搜索

计算智能的应用：药物设计、车间\物流调度、智慧水利、智能育种

国家自然科学基金面上项目,  多空间对齐的多目标智能药物分子设计方法与应用, 2025-2028, 在研, 主持

科技创新2030-“新一代人工智能”重大项目子课题, 基于多目标优化的可解释合成路线设计和平台搭建, 2024-2026, 在研, 主持

湖南省自然科学基金优青项目, 多目标智能优化, 2024-2026, 在研, 主持

国家自然科学基金青年项目, 面向多模态多目标组合优化问题的进化算法与应用, 2021-2024, 在研, 主持

湖南省自然科学基金青年项目, 学习引导的多模态多目标进化优化方法研究, 2020-2023, 已结题, 主持

本科 CS05102 人工智能

本科 CS06144 机器学习

博士 A2010007D 智能计算系统

本研究室招收博士后、博士及硕士研究生，也期待优秀的本科生加入。

欢迎计划在学术界或工业界长期发展的同学。期望我的学生从事高水平的科学研究，将自身的定位与眼光放在世界第一流团队的第一流工作上，做真正有国际影响力的工作。对于发表高水平论文的学生，将提供额外的科研奖励以及出国参会的支持。

2025年计划招收硕士生3名，博士生1名。

指导博士后：

2024级 Shah Fahad

指导博士生:

2023级 汪丽 (与日本筑波大学合作指导)

2024级 陈雨洁

指导硕士生：

2020级 许丽婷 (发表IEEE-TEVC (IF:16.497) 1篇，发表CCF C类1篇)

2021级 张昕怡 (发表IEEE-CIM (IF:9.809) 1篇, 投稿IEEE汇刊1篇)

2021级 张玲 (发表SWEVO (IF:10.0) 1篇, 投稿IEEE-TEVC 1篇，申请国家发明专利1项)

2022级 杨家豪 (投稿A类2篇，微软亚洲研究院实习)

2023级 刘翊纬 (发表CCF C类1篇)

2023级 于洲

2023级 肖宇航

2023级 张嘉仪 (投稿一区1篇)

2024级 卢桂东

2024级 林阿杰

2024级 郎展鹏

可参见我的Google学术主页

2024

Yiping Liu, Ling Zhang, Xiangxiang Zeng, Yuyan Han, “Evolutionary multimodal multiobjective optimization guided by growing neural gas,”Swarm and Evolutionary Computation 86 (2024) 101500.(2022IF: 10.0, 中科院SCI一区) 

Yiwei Liu, Yiping Liu*,Jiahao Yang, Xinyi Zhang, Li Wang, Xiangxiang Zeng,“Multi-Objective Molecular Design in Constrained Latent Space,”IJCNN 2024.(CCF-C)

Ning Cheng, Li Wang, Yiping Liu, Bosheng Song and Changsong Ding, “HANSynergy: Heterogeneous Graph Attention Network for Drug Synergy Prediction, Journal of Chemical Information and Modeling, 2024, online.(2022IF: 5.6, 中科院SCI二区)

2023

Yiping Liu, Liting Xu, Yuyan Han, Xiangxiang Zeng, Gary G Yenand Hisao Ishibuchi, “Evolutionary multimodal multiobjective optimization fortraveling salesman problems,” IEEE Transactions on Evolutionary Computation, 2023, Early Access, doi: 10.1109/TEVC.2023.3239546. (2022IF: 14.3, 中科院SCI一区)

Yiping Liu, Xinyi Zhang, Yuansheng Liu, Yansen Su, XiangxiangZeng and Gary G Yen, “Evolutionary Multi-Objective Optimization in Searchingfor Various Antimicrobial Peptides [Feature],” IEEE ComputationalIntelligence Magazine, vol. 18, no. 2, pp. 31–45, 2023. (2022IF: 9.0, 中科院SCI一区) (获测序中国与ScienceAI报道)

Yuansheng Liu, Xiangzhen Shen, Yongshun Gong, Yiping Liu, BoshengSong and Xiangxiang Zeng, “Sequence Alignment/Map format: a comprehensivereview of approaches and applications,” Briefings in Bioinformatics,vol. 24, no. 5, p. bbad320, 2023. (2022IF: 9.5, 中科院SCI一区)

Ying Xu, Chong Xu, Huan Zhang, Lei Huang, Yiping Liu, Yusuke Nojimaand Xiangxiang Zeng, “A multi-population multi-objective evolutionary algorithmbased on the contribution of decision variables to objectives for large-scalemulti/many-objective optimization,” IEEE Transactions on Cybernetics,vol. 53, no. 11, pp. 6998–7007, 2023. (2022IF: 11.8, 中科院SCI一区)

Yuhang Wang, Yuyan Han, Yuting Wang, Junqing Li, Kaizhou Gao and YipingLiu, “An effective two-stage iterated greedy algorithm for distributedflowshop group scheduling problem with setup time,” Expert Systems withApplications, vol. 233, p. 120909, 2023. (2022IF: 8.5, 中科院SCI一区)

Haoxiang Qin, Yuyan Han, Qingda Chen, Ling Wang, Yuting Wang, Junqing Liand Yiping Liu, “Energy-Efficient Iterative Greedy Algorithm for theDistributed Hybrid Flow Shop Scheduling with Blocking Constraints,” IEEETransactions on Emerging Topics in Computational Intelligence, vol. 7, no.5, pp. 1442–1457, 2023. (2022IF: 5.3, 中科院SCI二区)

Yusuke Nojima, Yuto Fujii, Naoki Masuyama, Yiping Liu and HisaoIshibuchi, “A Decomposition-based Multi-modal Multi-objective EvolutionaryAlgorithm with Problem Transformation into Two-objective Subproblems,”presented at the Proceedings of the Companion Conference on Genetic andEvolutionary Computation, 2023, pp. 399–402. (CCF-C类, 演化计算著名会议)

2022

Haoxiang Qin, Yuyan Han, Yuting Wang, Yiping Liu, Junqing Li andQuanke Pan, “Intelligent optimization under blocking constraints: A noveliterated greedy algorithm for the hybrid flow shop group scheduling problem,” Knowledge-BasedSystems, vol. 258, p. 109962, 2022. (2022IF: 8.8, 中科院SCI一区)

Haoxiang Qin, Yuyan Han, Biao Zhang, Leilei Meng, Yiping Liu, QuankePan and Dunwei Gong, “An improved iterated greedy algorithm for theenergy-efficient blocking hybrid flow shop scheduling problem,” Swarm andEvolutionary Computation, vol. 69, p. 100992, 2022. (2022IF: 10.0, 中科院SCI一区)

Haoxiang Qin, Yuyan Han, Yiping Liu, Junqing Li and Quanke Pan, “Acollaborative iterative greedy algorithm for the scheduling of distributedheterogeneous hybrid flow shop with blocking constraints,” Expert Systemswith Applications, vol. 201, p. 117256, 2022. (2022IF: 8.5, 中科院SCI一区)

Xue Han, Yuyan Han, Biao Zhang, Haoxiang Qin, Junqing Li, Yiping Liuand Dunwei Gong, “An effective iterative greedy algorithm for distributedblocking flowshop scheduling problem with balanced energy costs criterion,” AppliedSoft Computing, vol. 129, p. 109502, 2022. (2022IF: 8.7, 中科院SCI二区)

2021

Yiping Liu, Liting Xu, Yuyan Han, Naoki Masuyama, YusukeNojima, Hisao Ishibuchi and Gary G Yen, “Multi-modal multi-objective travelingsalesman problem and its evolutionary optimizer,” presented at the 2021 IEEEInternational Conference on Systems, Man, and Cybernetics (SMC), IEEE, 2021,pp. 770–777. (CCF-C类会议)

Xue Han, Yuting Wang, Yuyan Han, Yiping Liu and Hongyan Sang, “AnAlgorithm Based on Local Search for Solving Energy-efficient Distributed BlockingFlowshop Problems with Sequence-dependent Setup Times,” presented at the 20215th Asian Conference on Artificial Intelligence Technology (ACAIT), IEEE, 2021,pp. 266–275.

Xue Han, Yuyan Han, Yiping Liu, Quanke Pan, Haoxiang Qin and JunqingLi, “An improved iterated greedy algorithm for the distributed flow shopscheduling problem with sequence-dependent setup times,” presented at the 202111th International Conference on Information Science and Technology (ICIST),IEEE, 2021, pp. 332–340.

Xue Han, Yuyan Han, Qingda Chen, Junqing Li, Hongyan Sang, Yiping Liu,Quanke Pan and Yusuke Nojima, “Distributed flow shop scheduling withsequence-dependent setup times using an improved iterated greedy algorithm,” ComplexSystem Modeling and Simulation, vol. 1, no. 3, pp. 198–217, 2021.

2020

Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima andNaoki Masuyama, “Handling Imbalance Between Convergence and Diversity in theDecision Space in Evolutionary Multi-Modal Multi-Objective Optimization,” IEEETransactions on Evolutionary Computation, vol. 24, no. 3, pp. 551–565, 2020.(2022IF: 14.3, 中科院SCI一区)

Yiping Liu, Hisao Ishibuchi, Naoki Masuyama and YusukeNojima, “Adapting reference vectors and scalarizing functions by growing neuralgas to handle irregular Pareto fronts,” IEEE Transactions on EvolutionaryComputation, vol. 24, no. 3, pp. 439–453, 2020. (2022IF: 14.3, 中科院SCI一区)

Dunwei Gong, Yiping Liu* and Gary G Yen, “A meta-objective approachfor many-objective evolutionary optimization,” Evolutionary computation,vol. 28, no. 1, pp. 1–25, 2020. (CCF-B类, 演化计算著名期刊)

Yiping Liu, Hisao Ishibuchi, Gary G Yen, Yusuke Nojima, NaokiMasuyama and Yuyan Han, “On the normalization in evolutionary multi-modalmulti-objective optimization,” presented at the 2020 IEEE Congress onEvolutionary Computation (CEC), IEEE, 2020, pp. 1–8.

Junqing Li, Yunqi Han, Peiyong Duan, Yuyan Han, Ben Niu, Chengdong Li, ZhixinZheng and Yiping Liu, “Meta-heuristic algorithm for solving vehiclerouting problems with time windows and synchronized visit constraints inprefabricated systems,” Journal of Cleaner Production, vol. 250, p.119464, 2020. (2022IF: 11.1, 中科院SCI一区)

Yuyan Han, Junqing Li, Hongyan Sang, Yiping Liu, Kaizhou Gao andQuanke Pan, “Discrete evolutionary multi-objective optimization forenergy-efficient blocking flow shop scheduling with setup time,” AppliedSoft Computing, vol. 93, p. 106343, 2020. (2022IF: 8.7, 中科院SCI二区)

Yusuke Nojima, Takafumi Fukase, Yiping Liu, Naoki Masuyama and HisaoIshibuchi, “Constrained multiobjective distance minimization problems,”presented at the Proceedings of the Genetic and Evolutionary ComputationConference, 2019, pp. 586–594. (CCF-C类, 演化计算著名会议)

Narito Amako, Naoki Masuyama, Chu Kiong Loo, Yusuke Nojima, Yiping Liuand Hisao Ishibuchi, “Multilayer clustering based on adaptive resonance theoryfor noisy environments,” presented at the 2020 International Joint Conferenceon Neural Networks (IJCNN), IEEE, 2020, pp. 1–8. (CCF-C类会议)

2019

Yiping Liu, Gary G Yen and Dunwei Gong, “A multimodal multiobjectiveevolutionary algorithm using two-archive and recombination strategies,” IEEETransactions on Evolutionary Computation, vol. 23, no. 4, pp. 660–674,2019. (2022IF: 14.3, 中科院SCI一区)

Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyamaand Yuyan Han, “Searching for local pareto optimal solutions: A case study onpolygon-based problems,” presented at the 2019 IEEE Congress on EvolutionaryComputation (CEC), IEEE, 2019, pp. 896–903.

Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota, YusukeNojima and Yiping Liu, “Topological clustering via adaptive resonancetheory with information theoretic learning,” IEEE Access, vol. 7, pp.76920–76936, 2019. (2022IF: 3.9, 中科院SCI三区)

Yuyan Han, Junqing Li, Yiping Liu, Zhixin Zheng, Yuxia Pan, HongyanSang and Lili Liu, “Migrating Birds Optimization for Lot-streaming flow shopscheduling problem,” presented at the 2019 IEEE Congress on EvolutionaryComputation (CEC), IEEE, 2019, pp. 667–672.

Naoki Masuyama, Narito Amako, Yusuke Nojima, Yiping Liu, Chu KiongLoo and Hisao Ishibuchi, “Fast topological adaptive resonance theory based oncorrentropy induced metric,” presented at the 2019 IEEE Symposium Series onComputational Intelligence (SSCI), IEEE, 2019, pp. 2215–2221.

2018

Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyamaand Ke Shang, “A double-niched evolutionary algorithm and its behavior onpolygon-based problems,” presented at the Parallel Problem Solving fromNature–PPSN XV: 15th International Conference, Coimbra, Portugal, September8–12, 2018, Proceedings, Part I 15, Springer International Publishing, 2018,pp. 262–273. (CCF-B类, 演化计算著名会议)

Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyamaand Ke Shang, “Improving 1by1EA to handle various shapes of Pareto fronts,”presented at the Parallel Problem Solving from Nature–PPSN XV: 15thInternational Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings,Part I 15, Springer International Publishing, 2018, pp. 311–322. (CCF-B类, 演化计算著名会议)

Ke Shang, Hisao Ishibuchi, Min-Ling Zhang and Yiping Liu, “A new R2indicator for better hypervolume approximation,” presented at the Proceedingsof the Genetic and Evolutionary Computation Conference, 2018, pp. 745–752. (CCF-C类, 演化计算著名会议, Best Paper Award)

Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Yusuke Nojima and YipingLiu, “Topological Kernel Bayesian ARTMAP,” presented at the 2018 worldautomation congress (WAC), IEEE, 2018, pp. 1–5.

2018前

Yiping Liu, Dunwei Gong, Jing Sun and Yaochu Jin, “Amany-objective evolutionary algorithm using a one-by-one selection strategy,” IEEETransactions on Cybernetics, vol. 47, no. 9, pp. 2689–2702, 2017. (2022IF: 11.8,中科院SCI一区)

Yiping Liu, Dunwei Gong, Xiaoyan Sun and Yong Zhang,“Many-objective evolutionary optimization based on reference points,” AppliedSoft Computing, vol. 50, pp. 344–355, 2017. (2022IF: 8.7, 中科院SCI二区)

Xiaoyan Sun, Yang Chen, Yiping Liu and Dunwei Gong, “Indicator-basedset evolution particle swarm optimization for many-objective problems,” SoftComputing, vol. 20, pp. 2219–2232, 2016. (2022IF: 5.3, 中科院SCI三区)

Dunwei Gong, Yiping Liu*, Xinfang Ji and Jing Sun, “Evolutionaryalgorithms with user’s preferences for solving hybrid interval multi-objectiveoptimization problems,” Applied Intelligence, vol. 43, pp. 676–694,2015. (2022IF: 5.3, 中科院SCI二区)

巩敦卫, 刘益萍*, 孙晓燕, and 韩玉艳, “基于目标分解的高维多目标并行进化优化方法,” 自动化学报, vol. 41, no. 8, pp. 1438–1451, 2015. (DW Gong, YP Liu*, XY Sun andYY Han, “Parallel many-objective evolutionary optimization using objectivesdecomposition,” Acta Automatica Sinica, vol. 41, no. 8, pp. 1438–1451,2015.) (中文顶级期刊)

Yiping Liu, Dunwei Gong, Xiaoyan Sun and Yong Zhang, “Areference points-based evolutionary algorithm for many-objective optimization,”presented at the Proceedings of the Companion Publication of the 2014 AnnualConference on Genetic and Evolutionary Computation, 2014, pp. 1053–1056. (CCF-C类, 演化计算著名会议)