GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors

Mário Fernando da Silva Ventim Neves; Fernando José Almeida Vieira do Coito; Pedro Miguel Ribeiro Pereira; Maria Helena Silva Fino; DEE Group Author

doi:10.1007/978-3-642-11628-5_57

GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors

Mário Fernando da Silva Ventim Neves, Fernando José Almeida Vieira do Coito, Pedro Miguel Ribeiro Pereira, Maria Helena Silva Fino, DEE Group Author

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

This work introduces a tool for the optimization of CMOS integrated spiral inductors. The main objective of this tool is to offer designers a first approach for the determination of the inductor layout parameters. The core of the tool is a Genetic Algorithm (GA) optimization procedure where technology constraints on the inductor layout parameters are considered. Further constraints regarding inductor design heuristics are also accounted for. Since the layout parameters are inherently discrete due to technology and topology constraints, discrete variable optimization techniques are used. The Matlab GA toolbox is used and the modifications on the GA functions, yielding technology feasible solutions is presented. For the sake of efficiency and simplicity the pi-model is used for characterizing the inductor. The validity of the design results obtained with the tool, is checked against circuit simulation with ASITIC.

Original language	Unknown
Title of host publication	IFIP Advances in Information and Communication Technology
Editors	L Camarinha-Matos, P Pereira, L Ribeiro
Publisher	Springer Boston
Pages	515-522
Volume	314/20
ISBN (Print)	978-3-642-11627-8
DOIs	https://doi.org/10.1007/978-3-642-11628-5_57
Publication status	Published - 1 Jan 2010
Event	Doctoral Conference on Computing, Electrical and Industrial Systems - DoCEIS'10 - Duration: 1 Jan 2010 → …

Conference

Conference	Doctoral Conference on Computing, Electrical and Industrial Systems - DoCEIS'10
Period	1/01/10 → …

Access to Document

10.1007/978-3-642-11628-5_57

http://oa.uninova.pt/1947/

Cite this

Neves, M. F. D. S. V., Coito, F. J. A. V. D., Pereira, P. M. R., Fino, M. H. S., & DEE Group Author (2010). GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors. In L. Camarinha-Matos, P. Pereira, & L. Ribeiro (Eds.), IFIP Advances in Information and Communication Technology (Vol. 314/20, pp. 515-522). Springer Boston. https://doi.org/10.1007/978-3-642-11628-5_57

Neves, Mário Fernando da Silva Ventim ; Coito, Fernando José Almeida Vieira do ; Pereira, Pedro Miguel Ribeiro et al. / GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors. IFIP Advances in Information and Communication Technology. editor / L Camarinha-Matos ; P Pereira ; L Ribeiro. Vol. 314/20 Springer Boston, 2010. pp. 515-522

@inproceedings{5160889842f948c3b145599715441cf1,

title = "GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors",

abstract = "This work introduces a tool for the optimization of CMOS integrated spiral inductors. The main objective of this tool is to offer designers a first approach for the determination of the inductor layout parameters. The core of the tool is a Genetic Algorithm (GA) optimization procedure where technology constraints on the inductor layout parameters are considered. Further constraints regarding inductor design heuristics are also accounted for. Since the layout parameters are inherently discrete due to technology and topology constraints, discrete variable optimization techniques are used. The Matlab GA toolbox is used and the modifications on the GA functions, yielding technology feasible solutions is presented. For the sake of efficiency and simplicity the pi-model is used for characterizing the inductor. The validity of the design results obtained with the tool, is checked against circuit simulation with ASITIC.",

author = "Neves, {M{\'a}rio Fernando da Silva Ventim} and Coito, {Fernando Jos{\'e} Almeida Vieira do} and Pereira, {Pedro Miguel Ribeiro} and Fino, {Maria Helena Silva} and {DEE Group Author}",

year = "2010",

month = jan,

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doi = "10.1007/978-3-642-11628-5_57",

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editor = "L Camarinha-Matos and P Pereira and L Ribeiro",

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Neves, MFDSV , Coito, FJAVD , Pereira, PMR , Fino, MHS & DEE Group Author 2010, GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors. in L Camarinha-Matos, P Pereira & L Ribeiro (eds), IFIP Advances in Information and Communication Technology. vol. 314/20, Springer Boston, pp. 515-522, Doctoral Conference on Computing, Electrical and Industrial Systems - DoCEIS'10, 1/01/10. https://doi.org/10.1007/978-3-642-11628-5_57

GADISI - Genetic Algorithms Applied to the Automatic Design of Integrated Spiral Inductors. / Neves, Mário Fernando da Silva Ventim ; Coito, Fernando José Almeida Vieira do ; Pereira, Pedro Miguel Ribeiro et al.
IFIP Advances in Information and Communication Technology. ed. / L Camarinha-Matos; P Pereira; L Ribeiro. Vol. 314/20 Springer Boston, 2010. p. 515-522.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This work introduces a tool for the optimization of CMOS integrated spiral inductors. The main objective of this tool is to offer designers a first approach for the determination of the inductor layout parameters. The core of the tool is a Genetic Algorithm (GA) optimization procedure where technology constraints on the inductor layout parameters are considered. Further constraints regarding inductor design heuristics are also accounted for. Since the layout parameters are inherently discrete due to technology and topology constraints, discrete variable optimization techniques are used. The Matlab GA toolbox is used and the modifications on the GA functions, yielding technology feasible solutions is presented. For the sake of efficiency and simplicity the pi-model is used for characterizing the inductor. The validity of the design results obtained with the tool, is checked against circuit simulation with ASITIC.

AB - This work introduces a tool for the optimization of CMOS integrated spiral inductors. The main objective of this tool is to offer designers a first approach for the determination of the inductor layout parameters. The core of the tool is a Genetic Algorithm (GA) optimization procedure where technology constraints on the inductor layout parameters are considered. Further constraints regarding inductor design heuristics are also accounted for. Since the layout parameters are inherently discrete due to technology and topology constraints, discrete variable optimization techniques are used. The Matlab GA toolbox is used and the modifications on the GA functions, yielding technology feasible solutions is presented. For the sake of efficiency and simplicity the pi-model is used for characterizing the inductor. The validity of the design results obtained with the tool, is checked against circuit simulation with ASITIC.

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