Dynamic OHT routing using distance approximation based on deep neural network
- Title
- Dynamic OHT routing using distance approximation based on deep neural network
- Authors
- 유태영
- Date Issued
- 2021
- Publisher
- 포항공과대학교
- Abstract
- Recently, semiconductor fabrication plant has become larger and complex
to meet emerging market demand. This trend requires a massive number of
transportation moves in a huge rail network. The change of fab environment
brought two challenges: dynamic routing and scalable routing. In this thesis, a
dynamic OHT routing using distance approximation based on deep neural network is proposed to overcome these challenges. Proposed method consists of
local path finding model using shortest path finding approach, and global distance approximation model using deep learning approach. We report our computational results using high fidelity simulation experiments. In experiments,
proposed method shows better performance than other existing routing policy
and enough scalability .
- URI
- http://postech.dcollection.net/common/orgView/200000372235
https://oasis.postech.ac.kr/handle/2014.oak/111582
- Article Type
- Thesis
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