Email: guowk@swufe.edu.cn
个人简介
郭维康，沙巴体育app下载地址最新版教师，比利时根特大学博士，根特大学OR&S研究团队成员。在比利时根特大学和瑞典皇家理工学院KTH从事教学与科研工作期间，多次与来自比利时、瑞典、英国、德国、荷兰等多所世界知名高校和研究机构的专家合作，积累了丰富的学术与科研项目经验。
研究领域
机器学习，运筹学，智能决策，优化，项目调度等
社会兼职
担任European Journal of Operational Research (EJOR), Expert Systems with Applications (ESWA), Automation in Construction, Engineering Applications of Artificial Intelligence (EAAI), Applied Soft Computing (ASC), International Journal of Production Research (IJPR), Computers & Operations Research (COR), Computers & Industrial Engineering (CIE), Annals of Operations Research (AOR)等国际SCI学术期刊的特邀评审专家。
讲授课程
大数据基础，机器学习，数据挖掘，运筹学，项目管理, 操作系统，高性能计算，计算机基础，数据库原理等
部分研究成果
Books
l Weikang Guo. “Automatic detection of appropriate solution methods for the resource-constrained project scheduling problem via machine learning”. Ghent University Press, 2023.
Journal Articles
l Weikang Guo, Mario Vanhoucke, & José Coelho. “Learning to predict the best performing solution methods to solve single-project and multi-project scheduling problems”. Information Sciences (Impact factor: 8.2, JCR一区, 中科院SCI 一区, 计算机科学Top期刊), under review, 2024.
l Weikang Guo, Mario Vanhoucke, & José Coelho. “Comparison of problem transformation-based methods in detecting the best performing branch-and-bound procedures”. Expert Systems with Applications (Impact factor: 8.7, JCR一区, 中科院SCI 一区, 计算机科学Top期刊), under revision (5th round), 2023.
l Weikang Guo, Mario Vanhoucke, & José Coelho. “A prediction model for ranking branch-and-bound procedures for the resource-constrained project scheduling problem”. European Journal of Operational Research (Impact factor: 6.4, JCR一区, 中科院SCI 二区, 运筹学, 管理科学Top期刊), 306(2) 579-595, 2023.
l Weikang Guo, Mario Vanhoucke, José Coelho, & Jingyu Luo. “Automatic detection of the best performing priority rule for the resource-constrained project scheduling problem”, Expert Systems with Applications (Impact factor: 8.7, JCR一区, 中科院SCI 一区, 计算机科学Top期刊), 198, 116753, 2021.
l Jingyu Luo, Mario Vanhoucke, José Coelho, & Weikang Guo. “An efficient genetic programming approach to design priority rules for resource-constrained project scheduling problem”. Expert Systems with Applications (Impact factor: 8.7, JCR一区, 中科院SCI 一区, 计算机科学Top期刊), 167, 114116, 2022.
International Conferences
l Weikang Guo, Mario Vanhoucke, & José Coelho. “Performance comparison of machine learning models in detecting the best-performing methods for the resource-constrained single- and multi-project scheduling problem”, Presented at the 33rd European Conference on Operational Research (EURO 2024), Copenhagen, Denmark, 30th June - 3rd July, 2024.
l Weikang Guo, Mario Vanhoucke, & José Coelho. “Comparative study of two machine learning tasks in project scheduling”, Presented at the 18th International Workshop on Project Management and Scheduling (PMS2022), Ghent, Belgium, April 6 - 7, 2022.
l Weikang Guo, Mario Vanhoucke, & José Coelho. “A comparative study of machine learning methods to detect the best performing component for the resource-constrained project scheduling problem”, Presented at the INFORMS Annual Meeting 2021, Anaheim, California, USA, October 24 - 27, 2021.
l Weikang Guo, Mario Vanhoucke, & José Coelho. “Ranking components of the branch-and-bound procedure for the resource-constrained project scheduling problem via machine learning”, Presented at the 31st European Conference on Operational Research (EURO2021), Athens, Greece, July 11 - 14, 2021.
l Weikang Guo, Mario Vanhoucke, José Coelho, & Jingyu Luo. “Automatic detection of the best performance priority rule for resource-constrained project scheduling problem”, Presented at the 30th European Conference on Operational Research (EURO2019), Dublin, Ireland, June 23 - 26, 2019.
l Weikang Guo, Junhao Wen, Fengji Luo, & Yu Zheng. “Peak Load Reduction by Thermostatically Controlled Load Dispatch with Thermal Comfort Model”, the 10th IET International Conference on Advances in Power System Control, Operation and Management (APSCOM 2015), Hongkong, China, 8 - 12 November 2015.
科研项目
国家自然科学基金，面上项目，“移动环境下基于异构空间信息网络的社会化服务推荐研究“，2017至2020，62万 (人民币)，结题, 核心研究人员。
欧洲地平线项目，研究与创新项目，“基于人工智能实现云和HPC到边缘和物联网的自适应优化研究”，2023至2024，5 627 250,00 (欧元)，核心研究人员。
