Combining competitive scheme with slack neurons to solve real-time job scheduling problem

Ruey Maw Chen, Shih Tang Lo, Yueh Min Huang

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Generally, how to satisfy the deadline constraint is the major issue in solving real-time scheduling. Recently, neural network using competitive learning rule provides a highly effective method and deriving a sound solution for scheduling problem with less network complexity. However, due to the availability of resources, the machines may not reach full utilization. To facilitate the problem the extra neuron is introduced to the competitive neural network (CHNN). This study tries to impose slack neuron on CHNN with respect to process time and deadline constraints. Simulation results reveal that the competitive neural network imposed on the proposed energy function with slack neurons integrated ensures an appropriate approach of solving this class of scheduling problems of single or multiple identical machines.

Original languageEnglish
Pages (from-to)75-85
Number of pages11
JournalExpert Systems With Applications
Volume33
Issue number1
DOIs
Publication statusPublished - 2007 Jul 1

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Neurons
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Acoustic waves

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Cite this

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Combining competitive scheme with slack neurons to solve real-time job scheduling problem. / Chen, Ruey Maw; Lo, Shih Tang; Huang, Yueh Min.

In: Expert Systems With Applications, Vol. 33, No. 1, 01.07.2007, p. 75-85.

Research output: Contribution to journalArticle

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