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A Novel Bottom-left Packing Genetic Algorithm for Analog Module Placement : Volume 1, Issue 9 (05/05/2003)

By Zhang, L.

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Book Id: WPLBN0004002636
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: A Novel Bottom-left Packing Genetic Algorithm for Analog Module Placement : Volume 1, Issue 9 (05/05/2003)  
Author: Zhang, L.
Volume: Vol. 1, Issue 9
Language: English
Subject: Science, Advances, Radio
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Kleine, U., & Zhang, L. (2003). A Novel Bottom-left Packing Genetic Algorithm for Analog Module Placement : Volume 1, Issue 9 (05/05/2003). Retrieved from

Description: Otto-von-Guericke University of Magdeburg, IESK, PO Box 4120, D-39016 Magdeburg, Germany. This paper presents a novel genetic algorithm for analog module placement. It is based on a generalization of the two-dimensional bin packing problem. The genetic encoding and operators assures that all constraints of the problem are always satisfied. Thus the potential problems of adding penalty terms to the cost function are eliminated, so that the search configuration space decreases drastically. The dedicated cost function covers the special requirements of analog integrated circuits. A fractional factorial experiment was conducted using an orthogonal array to study the algorithm parameters. A meta-GA was applied to determine the optimal parameter values. The algorithm has been tested with several local benchmark circuits. The experimental results show this promising algorithm makes the better performance than simulated annealing approach with the satisfactory results comparable to manual placement.

A novel bottom-left packing genetic algorithm for analog module placement


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