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Neural computing for optimization and combinatorics

Author: Jun Wang; Yoshiyasu Takefuji
Publisher: Singapore ; River Edge, NJ : World Scientific, ©1996.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Since Hopfield proposed neural network computing for optimization and combinatorics problems, many neural network investigators have been working on optimization problems. In this book a variety of optimization problems and combinatorics problems are presented by respective experts. A very useful reference book for those who want to solve real-world applications, this book contains applications in graph theory,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Neural computing for optimization and combinatorics.
Singapore ; River Edge, NJ : World Scientific, ©1996
(DLC) 96196284
(OCoLC)34963867
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Jun Wang; Yoshiyasu Takefuji
ISBN: 9789812832122 9812832122
OCLC Number: 841172331
Description: 1 online resource (xiii, 230 pages) : illustrations
Contents: 1. N-queen and crossbar problems. 1.1. N-queen problems. 1.2. Mathematical neural network models. 1.3. N-queen neural network. 1.4. N-queen simulation programs. 1.5. Backtracking algorithm using prolog. 1.6. Crossbar switch scheduling. 1.7. References --
2. Gate packing problems. 2.1. Introduction. 2.2. Preliminary. 2.3. Gates packing problems. 2.4. Parallel algorithm. 2.5. Summary. 2.6. References --
3. Maximum clique problems: part 1. 3.1. Introduction. 3.2. Models of the processing element. 3.3. Maximum clique problems. 3.4. Maximum neural network. 3.5. Convergence property. 3.6. Parallel algorithm and simulation. 3.7. Conclusion. 3.8. References --
4. Maximum clique problems: part 2. 4.1. Introduction. 4.2. Neural network approach. 4.3. Simulation and conclusion. 4.4. References --
5. Multi-layer channel routing problems. 5.1. Introduction. 5.2. Definitions. 5.3. Algorithm. 5.4. Target machine. 5.5. Implementation. 5.6. Experimental results. 5.7. Conclusion. 5.8. Acknowledgement. 5.9. References --
6. Job-shop scheduling. 6.1. Introduction. 6.2. Job-shop scheduling. 6.3. Problem formulations. 6.4. Network architecture. 6.5. Network simulations. 6.6. Discussions. 6.7. Acknowledgements. 6.6. References --
7. BIBD problems. 7.1. BIBD problems. 7.2. Neural networks for BIBD problems. 7.3. References --
8. Discovering RNA interactions. 8.1. Introduction. 8.2. Maximum independent set programs. 8.3. Planarization and RNA structure prediction. 8.4. Real life analyses. 8.5. Additional problems. 8.6. References --
9. Missionaries and cannibals problems. 9.1. Introduction. 9.2. Parallel algorithm. 9.3. The tower of the Hanoi puzzle. 9.4. References --
10. Functional link nets. 10.1. Introduction. 10.2. Functional link net. 10.3. Optimization with functional link nets. 10.4. Conclusion. 10.5. References --
11. Identification and control. 11.1. Introduction. 11.2. Artificial neural networks. 11.3. The control problem. 11.4. Simulation example. 11.5. Results. 11.6. Conclusion. 11.7. Appendix. 11.8. References --
12. Ramsey numbers. 12.1. Introduction. 12.2. Ramsey number problems. 12.3. Results and discussion. 12.4. Conclusion. 12.5. References.
Responsibility: editors, Yoshiyasu Takefuji, Jun Wang.

Abstract:

This work presents a variety of optimization problems and combinatorics problems. It features applications in graph theory, mathematics, stochastic computing including the multiple relaxation,  Read more...

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