GALLO: a Genetic Algorithm for Floorplan Area Optimization
IEEE Transactions on Computer-Aided Design, August 1996, Vol. 15, No. 8, pp. 991-1000
The paper describes a Genetic Algorithm for the Floorplan Area Optimization problem. The algorithm is based on suitable techniques for solution encoding and evaluation function definition, effective cross-over and mutation operators, and heuristic operators which further improve the method's effectiveness. An adaptive approach automatically provides the optimal values for the activation probabilities of the operators. Experimental results show that the proposed method is competitive with the most effective ones as far as the CPU time requirements and the result accuracy is considered, but it presents some advantages: it requires a limited amount of memory, it is not sensible to special structures which are critical for other methods, and has a complexity which grows linearly with the number of implementations; finally, we demonstrate that the method is able to handle floorplans much larger (in terms of number of basic rectangles) than any benchmark previously considered in the literature.
|gallo.pdf||Adobe Acrobat portable document|
Copyright note for papers published by the IEEE Computer Society: Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE.
[RSeo96] M. Rebaudengo, M. Sonza Reorda, "GALLO: a Genetic Algorithm for Floorplan Area Optimization," IEEE Transactions on Computer-Aided Design, August 1996, Vol. 15, No. 8, pp. 991-1000