https://scholars.lib.ntu.edu.tw/handle/123456789/294634
Title: | SIMD Architecture for Job Shop Scheduling Problem Solving | Authors: | Kuan-Hung Chen SHI-CHUNG CHANG TZI-DAR CHIUEH Peter B. Luh Xing Zhao |
Issue Date: | May-2001 | Journal Volume: | 4 | Start page/Pages: | 530-533 | Source: | ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings | Abstract: | Job shop is a typical environment for manufacturing high-variety and low-volume discrete parts. Good scheduling is critical and challenging to the competitiveness of job shops. The Lagrangian relaxation neural network (LRNN) provides an approach of quantifiable quality and successful industrial applications. To further speed up scheduling for large-scale problems, in this paper, the parallelism of the LRNN approach is exploited for hardware implementation. New designs include a SIMD architecture, its associated instruction set and detailed circuits. Logic level simulation of the circuit design shows consistent schedules with those obtained by a software implementation. The hardware implementation is expected to have a one to two orders speed-up over the software one. © 2001 IEEE. |
URI: | http://scholars.lib.ntu.edu.tw/handle/123456789/294634 | DOI: | 10.1109/ISCAS.2001.922291 | SDG/Keyword: | Circuit designs; Hardware implementations; Instruction set; Job shop scheduling problems; Lagrangian relaxation neural networks; Large-scale problem; SIMD architecture; Software implementation; Computer software; Industrial applications; Integrated circuit manufacture; Scheduling; Hardware |
Appears in Collections: | 電機工程學系 |
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00922291.pdf | 451.96 kB | Adobe PDF | View/Open |
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