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

Expert Systems with Applications

Volumn 33, Issue 1, 2007, Pages 75-85

  Chen, Ruey Maw ^a   Lo, Shih Tang ^b   Huang, Yueh Min ^b  

^a NATIONAL CHIN YI UNIVERSITY OF TECHNOLOGY   (Taiwan)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Competitive learning; Hopfield neural network; Scheduling; Slack neuron

Indexed keywords

COMPUTER SIMULATION; CONSTRAINT THEORY; JOB ANALYSIS; PROBLEM SOLVING; REAL TIME SYSTEMS; SCHEDULING;

COMPETITIVE LEARNING; HOPFIELD NEURAL NETWORKS; SLACK NEURONS;

NEURAL NETWORKS;

EID: 33845665257     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2006.04.017     Document Type: Article

References (26)

1. Cardeira, C., & Mammeri, Z. (1994). Neural networks for multiprocessor real-time scheduling. In IEEE proceedings of the sixth Euromicro workshop on real-time systems (pp. 59-64).
2. Cardeira, C., & Mammeri, Z. (1996). Neural network versus max-flow algorithms for multi-processor real-time scheduling, real-time systems. In Proceedings of the eighth Euromicro workshop (pp. 175-180).
3. Cardeira, C., & Mammeri, Z. (1997). Handling precedence constraints with neural network based real-time scheduling algorithms. In Proceedings of ninth Euromicro workshop on real-time systems (pp. 207-214).
4. Chen, R. M., & Huang, Y. M. (1998). Multiconstraint task scheduling in multiprocessor system by neural network. In Proceedings of the IEEE tenth international conference on tools with artificial intelligence, Taipei (pp. 288-294).
5. Chen R.M., and Huang Y.M. Competitive neural network to solve scheduling problem. Neurocomputing 37 1-4 (2001) 177-196
6. Chung P.C., Tsai C.T., Chen E.L., and Sun Y.N. Polygonal approximation using a competitive Hopfield neural network. Pattern Recognition 27 (1994) 1505-1512
7. Cohen M., and Grossberg S. Absolute stability of goal pattern formation and parallel memory storage by competitive neural network. IEEE Transaction on System, Man, and Cybernetics 13 (1983) 815-826
8. Dixon, M. W., Cole, G. R., & Bellgard, M. I. (1995). Using the Hopfield model with mean-field annealing to solve the routing problem in a communication network. In International conference on neural networks (vol. 5, pp. 2652-2657).
9. Foo, Y. P. S., & Takefuji, T. (1998). Integer linear programming neural networks for job-shop scheduling. In IEEE international conference on neural networks (vol. 2, pp. 341-348).
10. Hanada, A., & Ohnishi, K. (1993). Near optimal jobshop scheduling using neural network parallel computing. In Proceedings of the international conference on industrial electronics, control, and instrumentation (vol. 1, pp. 315-320).
11. Hopfield J.J. Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Science 79 (1982) 2554-2558
12. Hopfield J.J. Neurons with graded response have collective computational properties like those of two-state neurons. Proceedings of the National Academy of Science 81 (1984) 3088-3092
13. Hopfield J.J., and Tank D.W. Neural computation of decision in optimization problems. Biological Cybernetics 52 (1985) 141-152
14. Hopfield J.J., and Tank D.W. Computing with neural circuits: A model. Science 233 (1986) 625-633
15. Huang Y.M., and Chen R.M. Scheduling multiprocessor job with resource and timing constraints using neural network. IEEE Transactions on System, Man and Cybernetics, Part B 29 4 (1999) 490-502
16. Lee K.C., Funabiki N., and Takefuji Y. A parallel improvement algorithm for the bipartite subgraph problem. IEEE Transactions on Neural Networks 3 1 (1992) 139-145
17. Liu C., and Layland J. Scheduling algorithms for multiprogramming in a hard real-time environment. Journal of the ACM 20 l (1973) 46-61
18. Park, J. G., Park, J. M., Kim, D. S., Lee, C. H., Suh, S. W., & Han, M. S. (1994). Dynamic neural network with heuristic. In IEEE international conference on neural networks (vol. 7, pp. 4650-4654).
19. Silva, M. P., Cardeira, C., & Mammeri Z. (1997). Solving real-time scheduling problems with Hopfield-type neural networks. In EUROMICRO'97 new frontiers of information technology, proceedings of the 23rd EUROMICRO conference (pp. 671-678).
20. Tagliarini G.A., Christ J.F., and Page E.W. Optimization using neural networks. IEEE Transaction on Computers 40 12 (1991) 1347-1358
21. Takeda M., and Goodman J.W. Neural networks for computation: number representation and programming complexity. Applied Optics 25 (1986) 3033-3046
22. Takefuji Y., and Lee K.C. An artificial hysteresis binary neuron: a model suppressing the oscillatory behaviors of neuron dynamics. Biological Cybernetics 64 (1991) 353-356
23. Tank D., and Hopfield J.J. Simple neural optimization networks: an A/D converter, signal decision circuit and a linear programming circuit. IEEE Transactions on Circuits and Systems 33 5 (1986) 533-541
24. Uchiyama T., and Arbib M.A. Color image segmentation using competitive learning. IEEE Transactions on Pattern Analysis Machine Intelligence 16 12 (1994) 1197-1206
25. Willems T.M., and Rooda J.E. Neural networks for job-shop scheduling. Control Engineering Practice 2 1 (1994) 31-39
26. Zhang, C. S., Yan, P. F., & Chang, T. (1991). Solving job-shop scheduling problem with priority using neural network. In IEEE international conference on neural networks (pp. 1361-1366).