MSO Lab is an in-depth research unit of Optimization. The main research areas of MSO Lab include: Artificial Intelligence and Machine Learning, Algorithms and Optimization, High Performance Computing. MSO Lab guides basic research and publishes research results in leading international journals and conferences. MSO Lab will pioneer the applications of basic algorithms and optimization researches to solve practical problems such as logistics, scheduling, intelligent systems, network design problems, and sensor networks optimization problems.
MSO Lab cooperates with strong research teams of foreign universities such as Melbourne University, University of Sydney, Nanyang Technological University, and some Vietnamese international corporations such as Cinnamon, DAC, etc.
MSO Lab has been presiding over 04 National Foundation of Science and Technology projects (NAFOSTED) cooperating with Belgium and Germany partners, 02 Ministerial-level Research projects, 01 State-level Research project, 01 International collaboration projects sponsored by US Army Research Lab.
News
August 16, 2018
Team from MSO Lab has 3 papers accepted at IEEE World Congress on Computational Intelligence (WCCI). We also participated WCCI2018…
March 30, 2018
Thời gian: 14.00 ngày 29/3/2018 Địa điểm: phòng seminar tầng 9 (MICA) Người trình bày: Prof. Pierre Divenyi, Stanford University Title: The…
March 26, 2018
Ergonomic Aspects of Autonomous Driving Studying Human Behavior in Urban Traffic Using Linked Driving Simulation Thời gian: 14.30 ngày thứ…
November 3, 2017
Thời gian: 14.30 ngày thứ 2, 6/11/2017 Địa điểm: phòng 803, nhà B1, Đại học Bách khoa Hà Nội Người…
Recent publications
2020 |
Binh, Huynh Thi Thanh; Hanh, Nguyen Thi ; Quan, La Van ; Nghia, Nguyen Duc ; Dey, Nilanjan Metaheuristics for maximization of obstacles constrained area coverage in heterogeneous wireless sensor networks Journal Article Appl. Soft Comput., 86 , 2020. @article{DBLP:journals/asc/BinhHQND20, title = {Metaheuristics for maximization of obstacles constrained area coverage in heterogeneous wireless sensor networks}, author = {Huynh Thi Thanh Binh and Nguyen Thi Hanh and La Van Quan and Nguyen Duc Nghia and Nilanjan Dey}, url = {https://doi.org/10.1016/j.asoc.2019.105939}, doi = {10.1016/j.asoc.2019.105939}, year = {2020}, date = {2020-01-01}, journal = {Appl. Soft Comput.}, volume = {86}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Ha, Quang Minh; Deville, Yves ; Dung, Pham Quang ; Hà, Minh Hoàng A hybrid genetic algorithm for the traveling salesman problem with drone Journal Article J. Heuristics, 26 (2), pp. 219–247, 2020. @article{DBLP:journals/heuristics/HaDDH20, title = {A hybrid genetic algorithm for the traveling salesman problem with drone}, author = {Quang Minh Ha and Yves Deville and Pham Quang Dung and Minh Hoàng Hà}, url = {https://doi.org/10.1007/s10732-019-09431-y}, doi = {10.1007/s10732-019-09431-y}, year = {2020}, date = {2020-01-01}, journal = {J. Heuristics}, volume = {26}, number = {2}, pages = {219--247}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
2019 |
Nguyen, Thi Tam; Binh, Huynh Thi Thanh ; Dung, Dinh Anh ; Lan, Phan Ngoc ; Le, Vinh Trong ; Yuan, Bo ; Yao, Xin A hybrid clustering and evolutionary approach for wireless underground sensor network lifetime maximization Journal Article Inf. Sci., 504 , pp. 372–393, 2019. @article{DBLP:journals/isci/NguyenBDLLYY19, title = {A hybrid clustering and evolutionary approach for wireless underground sensor network lifetime maximization}, author = {Thi Tam Nguyen and Huynh Thi Thanh Binh and Dinh Anh Dung and Phan Ngoc Lan and Vinh Trong Le and Bo Yuan and Xin Yao}, url = {https://doi.org/10.1016/j.ins.2019.07.060}, doi = {10.1016/j.ins.2019.07.060}, year = {2019}, date = {2019-01-01}, journal = {Inf. Sci.}, volume = {504}, pages = {372--393}, keywords = {}, pubstate = {published}, tppubtype = {article} } |