Minimizing makespan on identical parallel machines using neural networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4234 LNCS - III, Issue , 2006, Pages 553-562

  Akyol, Derya Eren ^a   Bayhan, G Mirac ^a  

^a DOKUZ EYLUL UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; DATA REDUCTION; JOB ANALYSIS; NEURAL NETWORKS; OPTIMIZATION; PROBLEM SOLVING;

ENERGY FUNCTIONS; PARALLEL MACHINES; PENALTY COEFFICIENTS;

DISTRIBUTED COMPUTER SYSTEMS;

EID: 33750686925     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11893295_61     Document Type: Conference Paper

References (20)

1. Aiyer, S.V.B., Niranjan, M., Fallside, F.: A theoretical investigation into the performance of the Hopfield model. IEEE Transactions on Neural Networks. 1 (1990) 204-215
2. Akiyama, Y., Yamashita, A., Kajiura, M., Aiso, H.: Combinatorial Optimization with Gaussian Machines. Proceedings IEEE International Joint Conference on Neural Networks. 1 (1989) 533-540
3. Brandt, R.D., Wang, Y., Laub, A.J., Mitra, S.K.: Alternative Networks for Solving the Travelling Salesman Problem and the List-Matching Problem. Proceedings of the International Conference on Neural Networks. 2 (1988) 333-340
4. Cheng, T., Sin, C.: A State-of-the-Art Review of Parallel-Machine Scheduling Research. European Journal of Operation Research. 47 (1990) 271-292
5. Coffman, E.G., Garey, M.R., Johnson, D.S.: An application of bin-packing to multi-processor scheduling. SIAM Journal of Computing. 7 (1978) 1-17
6. Dogan, H., Guzelis, C.: (accepted paper) A new approach based on a time varying penalty parameter providing robustness and fuzziness in spherical clustering. IEEE Transactions on Circuits and Systems-II
7. Graham, R.L.: Bounds on multiprocessor timing anomalies. SIAM Journal of Applied Mathematics. 17 (1969) 416-429
8. Graham, R.L., Lawler, E.L., Lenstra, J.K., Rinnooy Kan A.H.G.: Optimization and approximation in deterministic sequencing and scheduling: A survey. Annals of Discrete Mathematics. 5 (1979) 287-326
9. Hedge, S., Sweet, J., Levy, W.: Determination of parameters in a Hopfield/Tank computational network. Proceedings IEEE International Conference on Neural Networks. 2 (1988) 291-298
10. Hinton, G.E., Sejnowski, T.J.: Learning and relearning in Boltzmann machines. In: D.E. Rumelhart, & J.L. McClelland, Parallel Distributed Processing: Explorations in Microstructure of Cognition. Cambridge: MIT Press. (1986)
11. Hopfield, J.: Neurons with graded response have collective computational properties like of two-state neurons. Proceedings of the National Academy of Sciences of the USA. 81 (1984) 3088-3092
12. Hopfield, J., Tank, T.W.: Neural computation of decisions in optimization problems, Biological Cybernetics. 52 (1985) 141-152
13. Kamgar-Parsi, B., Kamgar-Parsi, B.: Dynamical Stability and Parameter Selection in Neural Optimization. Proceedings of International Joint Conference on Neural Networks. 4 (1992) 566-571
14. Lai, W.K., Coghill, G.G.: Genetic Breeding of Control Parameters for the Hopfield/Tank Neural Net. Proceedings of the International Joint Conference on Neural Networks. 4 (1992) 618-623
15. Mokotoff, E.: Paralel Machine Scheduling Problems: A Survey. Asia-Pacific Journal of Operational Research. 18 (2001) 193-242
16. Peterson, C., Anderson, J.R.: A mean-field theory learning algorithm for neural networks. Complex Systems. 1 (1987) 995-1019
17. Smith, K. A.: Neural Networks for Combinatorial Optimization: A Review of More Than a Decade of Research. INFORMS Journal on Computing. 11 (1999) 15-34
18. Van Den Bout, D.E., Miller, T.K.: A Traveling Salesman Objective Function that Works. Proceedings of IEEE International Conference on Neural Networks. 2 (1988) 299-303
19. Wang, J.: A Time-Varying Recurrent Neural System for Convex Programming. Proceedings of UCNN-91-Seattle International Joint Conference on Neural Networks. (1991) 147-152
20. Watta, P.B., Hassoun, M.H.: A Coupled Gradient Network Approach for Static and Temporal Mixed-Integer Optimization. IEEE Transactions on Neural Networks. 7 (1996) 578-593