Travelled to:1 × China
1 × Italy
1 × Korea
2 × USA
Collaborated with:M.Inuiguchi Y.Hiranaka I.Matsumoto R.Maeno S.Yin T.Izuno Y.Tanaka Ryotaro Yamazaki Soh Sakurai Yoki Matsuoka Kevin Tiemey I.E.Grossmann T.Sugiyama S.Takahashi K.Ueda
Talks about:decomposit (6) problem (6) approach (5) schedul (5) petri (4) rout (4) net (4) simultan (3) method (3) product (2)
Person: Tatsushi Nishi
DBLP: Nishi:Tatsushi
Contributed to:
2012201120082007200620172019Wrote 9 papers:
- CASE-2012-MatsumotoN #approach #clustering #composition #concurrent #petri net #scheduling #tool support
- Petri net decomposition approach to deadlock-free scheduling for dual-armed cluster tools (IM, TN), pp. 194–199.
- CASE-2012-SugiyamaNITU #approach #composition #problem
- A bilevel decomposition approach to railway crew rostering problems for fair labor condition (TS, TN, MI, ST, KU), pp. 383–389.
- CASE-2011-NishiYI #approach #generative #problem #scheduling
- Column generation approach to ship scheduling problems for international crude oil transportation (TN, SY, TI), pp. 468–473.
- CASE-2008-NishiTI #approach #automation #composition #optimisation #petri net
- Petri Net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles (TN, YT, MI), pp. 175–180.
- CASE-2007-NishiHI #problem #scheduling
- A Successive Lagrangian Relaxation Method for Solving Flowshop Scheduling Problems with Total Weighted Tardiness (TN, YH, MI), pp. 875–880.
- CASE-2007-NishiHIG #composition #generative #multi #scheduling
- A Decomposition Method with Cut Generation for Simultaneous Production Scheduling and Routing for multiple AGVs (TN, YH, MI, IEG), pp. 658–663.
- CASE-2006-NishiM #composition #optimisation #petri net #problem
- Decomposition of Petri Nets for Optimization of Routing Problem for AGVs in Semiconductor Fabrication Bays (TN, RM), pp. 236–241.
- CASE-2017-YamazakiNS #abstraction #composition #first-order #hybrid #petri net #problem
- A decomposition method with discrete abstraction for simultaneous traffic signal control and route selection problem with first-order hybrid Petri Nets (RY, TN, SS), pp. 352–357.
- CASE-2019-MatsuokaNT #approach #identification #machine learning #problem #scheduling
- Machine Learning Approach for Identification of Objective Function in Production Scheduling Problems (YM, TN, KT), pp. 679–684.