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Solving Sequencing Problems Using Recurrent Neural Networks and Simulated Annealing - A Structural and Computational Comparison -

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Operations Research Proceedings 1994

Part of the book series: Operations Research Proceedings ((ORP,volume 1994))

Summary

Since most sequencing problems are NP-hard, many heuristic techniques have been tried to solve such problems. In this paper, we investigate two methods - Hopfield neural networks and Simulated Annealing - and their application to the problem of placing standard cells during VLSI design. Comparisons were made with respect to solution quality and computing time. Simulated Annealing performed better in all test cases, but the differences between solution qualities decrease as problem sizes and complexities are higher. Advantages and disadvantages of both methods, and approaches to improve their performance are discussed.

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References

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© 1995 Springer-Verlag Berlin Heidelberg

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Singh, K., Schneider, B., Kurbel, K. (1995). Solving Sequencing Problems Using Recurrent Neural Networks and Simulated Annealing - A Structural and Computational Comparison -. In: Derigs, U., Bachem, A., Drexl, A. (eds) Operations Research Proceedings 1994. Operations Research Proceedings, vol 1994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79459-9_72

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  • DOI: https://doi.org/10.1007/978-3-642-79459-9_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58793-4

  • Online ISBN: 978-3-642-79459-9

  • eBook Packages: Springer Book Archive

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