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Micro-scale truss optimization using genetic algorithm

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Abstract

This paper describes the development of a genetic algorithm that is capable of optimizing the mass of micro-scale trusses. Belonging to the group of periodic cellular materials, micro-scale trusses are characterized by the creation of a base cell with a pattern that is repeated in space until a global structure is obtained. Investigation in this field has generally been focused on the design of base cells and their resistance once the final structure is obtained. In this project we have attempted to optimize each individual cell and in particular its elements according to the loads and boundary conditions applied to the global structure. With this objective, we defined a dichotomic search algorithm that establishes a set of cross-sectional areas suitable for the micro-scale truss, formulated the penalty coefficient for the over-sized elements, and studied the clones and rebirth process in order to avoid stagnation of the genetic algorithm. The cell elements used in this project were equal to or less than to 1 mm long, with a cross-sectional area in the order of 10 − 9 m2.

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Acknowledgments

The work described in this paper was supported by a grant from the Spanish Ministerio de Educacion y Ciencia through the National Programme of Mobility of Human Resources del Plan Nacional de I-D+I 2008–2011.

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Authors and Affiliations

  1. Construction and Production Engineering Department, University of Oviedo, Mieres, Spain

    María Belén Prendes-Gero

  2. Département de Génie Mécanique, Université de Sherbrooke, Sherbrooke, QC, Canada

    Jean-Marc Drouet

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  1. María Belén Prendes-Gero
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  2. Jean-Marc Drouet
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Correspondence to María Belén Prendes-Gero.

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Prendes-Gero, M.B., Drouet, JM. Micro-scale truss optimization using genetic algorithm. Struct Multidisc Optim 43, 647–656 (2011). https://doi.org/10.1007/s00158-010-0603-x

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  • DOI: https://doi.org/10.1007/s00158-010-0603-x

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