SIMD Architecture for Job Shop Scheduling Problem Solving
Journal
ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings
Journal Volume
4
Pages
530-533
Date Issued
2001-05
Author(s)
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.
SDGs
Other Subjects
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
Type
conference paper
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