Ph.D. (Informatics), Professor,
Endowed Research Laboratory in Mathematical Optimization, Department of Information and Physical Sciences, Graduate School of Information Science and Technology, Osaka University.
Mathematical optimization gives us powerful solutions to tackle a wide variety of real applications with large-scale data. However, most of these problems are classified into the class of NP-hard from the view of computational complexity. Under the background, we are aiming to develop practical algorithms for harder and larger combinatorial optimization problems within reasonable computation time.
The current research topics are as follows:
Automatic algorithm configuration to improve the performance of general-purpose heuristic solvers
Heuristic algorithms for large-scale combinatorial optimization problems
Packing and cutting problems and their applications
Mathematical optimization models and algorithms for solving real applications
2021/4/13, We have uploaded the following preprint.
S.Umetani and S.Murakami, Coordinate descent heuristics for the irregular strip packing problem of rasterized shapes, arXiv preprints, arXiv:2104.04525, 2021. paper
2020/10/1, The endowed research laboratory in mathematical Optimization has been established, donated by BrainPad Inc. and Fujitsu Laboratories Ltd.
2020/5/6, Our paper has been published in the Journal of the Operations Research Society of Japan (JORSJ).
N.Uematsu, S.Umetani and Y.Kawahara, An efficient branch-and-cut algorithm for submodular function maximization, Journal of the Operations Research Society of Japan, 63 (2020), 41-59. DOI: 10.15807/jorsj.63.41 (open access) supplement
2019/10/1, We have sent a press release about collaboration with TOKYO-Mitsui O.S.K. Lines, Ltd.
MOL Group Successfully Develops Car Carrier Allocation/Loading Plan with Fundamental technologies of AI — Significantly Improving Efficiency in Planning and Validation with 'Mathematical Optimization' — press release
2019/8/5, Our paper has been accepted for publication in the Journal of the Operations Research Society of Japan (JORSJ).
An efficient branch-and-cut algorithm for submodular function maximization
2019/6/23, Our paper has been accepted for publication at IEEE SMC 2019 Conference.
An efficient branch-and-cut algorithm for approximately submodular function maximization
Address: 2-1 Yamadaoka, Suita, Osaka 565-0871, JAPAN.
Tel: +81-6-6879-4793 (direct)