no code implementations • 8 Jan 2024 • Joshua Levin, Randall Correll, Takanori Ide, Takafumi Suzuki, Takaho Saito, Alan Arai
With the goal of making deep RL a viable strategy for real-world industrial-scale supply chain logistics, we develop new extensions to existing encoder-decoder attention models which allow them to handle multiple trucks and multi-leg routing requirements.
no code implementations • 30 Nov 2022 • Randall Correll, Sean J. Weinberg, Fabio Sanches, Takanori Ide, Takafumi Suzuki
We use reinforcement learning with neural networks with embedded quantum circuits.
no code implementations • 30 Nov 2022 • Randall Correll, Sean J. Weinberg, Fabio Sanches, Takanori Ide, Takafumi Suzuki
With the aim of making reinforcement learning a viable technique for supply chain optimization, we develop new extensions to encoder-decoder models for vehicle routing that allow for complex supply chains using classical computing today and quantum computing in the future.
no code implementations • LREC 2012 • Takafumi Suzuki, Yusuke Abe, Itsuki Toyota, Takehito Utsuro, Suguru Matsuyoshi, Masatoshi Tsuchiya
In order to organize Japanese functional expressions with various surface forms, a lexicon of Japanese functional expressions with hierarchical organization was compiled.