Stochastic neural networks for solving job-shop scheduling. I. Problem representation

  title={Stochastic neural networks for solving job-shop scheduling. I. Problem representation},
  author={Foo Yoon-Pin Simon and Y. Takefuji},
  journal={IEEE 1988 International Conference on Neural Networks},
  pages={275-282 vol.2}
An application of neural networks is presented for solving job-shop scheduling, and NP-complete optimization problem with constraint satisfaction. In particular, the authors introduce a neural computation architecture based on a stochastic Hopfield neural-network model. First, the job-shop problem is mapped into a two-dimensional matrix representation of neurons similar to those for solving the traveling salesman problem (TSP). Constant positive and negative current biases are applied to… CONTINUE READING
Highly Cited
This paper has 48 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 29 extracted citations


Publications referenced by this paper.
Showing 1-4 of 4 references

Page, "Solving Constraint Satisfaction Problems with Neural Networks

  • E. W. G A . Tagliarini
  • IEEE 1 s t Int. Conf. on Neural Networks,
  • 1987


  • J. J. Hopfield, D.W
  • "Computing with Neural Circuits: A Model…
  • 1986

Introduction to Sequencing and Scheduling,

  • K. R. Baker
  • 1974

Similar Papers

Loading similar papers…