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logo SMC logo SMC  OPTI MVMO Museum_Washington Multivariate and multi-objective optimization
Contact Manuel Herrera, Rajan Filomeno Coelho
Keywords metamodels, mixed variables, categorical variables, multi-objective, multicriteria
  • Prof. M. Xiao, Prof. W. Zhang (Northwestern Polytechnical University, Xi'an, China)
Multivariate and multi-objective optimization Nowadays, civil and architectural engineers are confronted to increasing demands to reduce the cost of lightweight structures, while accounting for the environmental impact, the safety, and the comfort, and (last but not least) by attempting to propose innovative and inspiring designs. For that multifaceted purpose, multi-objective optimization offers a comprehensive set of methods to get the best compromise solutions at a lower computational cost.

Beside multiple objectives, engineering design is also often characterized by several types of variables: continuous (e.g. geometrical dimensions), discrete or integer (e.g. cross-section areas from a catalog, number of layers in a composite), or even categorical (e.g. type of material: "steel", "timber", "aluminum").

Therefore, one research axis investigated in BATir-SMC consists in developing evolutionary algorithms for multiple objectives and mixed variables.

This work is done in collaboration with the Northwestern Polytechnical University (Xi'an, China).

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Selected publications
  • [1] R Filomeno Coelho. Metamodels formixed variables based onmoving least squares–Application to the structural analysis of a rigid frame. Optimization and Engineering, 2013.
  • [2] R Filomeno Coelho and Ph Bouillard. Multi-objective reliability-based optimization with stochastic metamodels. Evolutionary Computation, 19(4):525–560, 2011.