The Placement of Electronic Circuits Problem: A Neural Network Approach

M. Ettaouil; K. Elmoutaouakil; Y. Ghanou

Mathematical Modelling of Natural Phenomena (2010)

  • Volume: 5, Issue: 7, page 109-115
  • ISSN: 0973-5348

Abstract

top
The goal of this paper is to apply the Continuous Hopfield Networks (CHN) to the Placement of Electronic Circuit Problem (PECP). This assignment problem has been expressed as Quadratic Knapsack Problem (QKP). To solve the PECP via the CHN, we choose an energy function which ensures an appropriate balance between minimization of the cost function and simultaneous satisfaction of the PECP constraints. In addition, the parameters of this function must avoid some bad local minima. Finally, some computational experiments solving the PECP are included

How to cite

top

Ettaouil, M., Elmoutaouakil, K., and Ghanou, Y.. Taik, A., ed. "The Placement of Electronic Circuits Problem: A Neural Network Approach." Mathematical Modelling of Natural Phenomena 5.7 (2010): 109-115. <http://eudml.org/doc/197636>.

@article{Ettaouil2010,
abstract = {The goal of this paper is to apply the Continuous Hopfield Networks (CHN) to the Placement of Electronic Circuit Problem (PECP). This assignment problem has been expressed as Quadratic Knapsack Problem (QKP). To solve the PECP via the CHN, we choose an energy function which ensures an appropriate balance between minimization of the cost function and simultaneous satisfaction of the PECP constraints. In addition, the parameters of this function must avoid some bad local minima. Finally, some computational experiments solving the PECP are included},
author = {Ettaouil, M., Elmoutaouakil, K., Ghanou, Y.},
editor = {Taik, A.},
journal = {Mathematical Modelling of Natural Phenomena},
keywords = {placement of the electronic circuits problem (PECP); continuous Hopfield networks (CHN); quadratic Knapsack problem (QKP); combinatorial problems},
language = {eng},
month = {8},
number = {7},
pages = {109-115},
publisher = {EDP Sciences},
title = {The Placement of Electronic Circuits Problem: A Neural Network Approach},
url = {http://eudml.org/doc/197636},
volume = {5},
year = {2010},
}

TY - JOUR
AU - Ettaouil, M.
AU - Elmoutaouakil, K.
AU - Ghanou, Y.
AU - Taik, A.
TI - The Placement of Electronic Circuits Problem: A Neural Network Approach
JO - Mathematical Modelling of Natural Phenomena
DA - 2010/8//
PB - EDP Sciences
VL - 5
IS - 7
SP - 109
EP - 115
AB - The goal of this paper is to apply the Continuous Hopfield Networks (CHN) to the Placement of Electronic Circuit Problem (PECP). This assignment problem has been expressed as Quadratic Knapsack Problem (QKP). To solve the PECP via the CHN, we choose an energy function which ensures an appropriate balance between minimization of the cost function and simultaneous satisfaction of the PECP constraints. In addition, the parameters of this function must avoid some bad local minima. Finally, some computational experiments solving the PECP are included
LA - eng
KW - placement of the electronic circuits problem (PECP); continuous Hopfield networks (CHN); quadratic Knapsack problem (QKP); combinatorial problems
UR - http://eudml.org/doc/197636
ER -

References

top
  1. A. Cichocki, R. Unbehauen. Neural networks for optimization and signal processing. B.G. Teubner Stuttgart, 1993.  
  2. M. Ettaouil. Contribution à l’étude des problèmes de satisfaction de contraintes et à la programmation quadratiques en nombre entiers, allocation statiques de tâches dans les systèmes distrubués, thèse d’état, Université Sidi Mohammed ben Abdellah, F.S.T. de Fès, 1999.  
  3. M. Ettaouil, Y. Ghanou. Neural architectures optimization and Genetic algorithms. Wesas Trasactions on Computer, 3 (2009), No. 8, 526-537. 
  4. A.H. Gee, S.V.B. Aiyer, R.W. Prager. An analytical framework for optimizing neural networks. Neural Networks, (1993), No. 6, 79-97. 
  5. A. Ghosh, S.K. Pal. Object Background classification using Hopfield type neural networks. International Journal of Patten Recognition and Artificial Intelligence, (1992), No. 6, 989-1008. 
  6. J.J. Hopfield, D.W. Tank. Neural computation of decisions in optimisation problems. Biological Cybernetics, 52 (1985), 1-25. 
  7. J.J. Hopfield. Neurons with graded response have collective computational properties like those of two-states neurons. Proceedings of the National Academy of Sciences of USA, 81 (1984), 3088-3092. 
  8. M. Jünger, A. Martin, G. Reinel, R. Weismantel. Quadratic 0/1 optimization and a decomposition approach for the placement of electronic circuits. Report 91. 102, Institut für Informatik Universität köln, (1991).  
  9. B.W. Lee, B.J. Shen. Hardware annealing in electronic neural networks. IEEE Trans, 1 (1990), 134 
  10. N.M. Nasrabadi, C.Y. Choo. Hopfield network for stereo vision correspondence, New York: Marcel Dekker, 1994.  
  11. P.M. Talavàn, J. Yànez. A continuous Hopfield network equilibrium points algorithm. Computers and Operations Research, 32 (2005), 2179-2196. 
  12. K. Tatsumi, Y. Yagi, T. Tanino. Improved projection Hopfield network for the quadratic assignment problem. SICE 2002, proceedings of the 41 st SICE annual conference, 4 (2002), 2295-2300. 

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.