Optimum Structural Design Using Bio-Inspired Search Methods: A Survey and Applications

Computational Methods in Applied Sciences

Galván

et al. 2015

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The optimization structural design problems of Fully Stressed Design (FSD) and Minimum Constrained Weight (MCW) are compared in this work in a simple truss test case with discrete cross-section type bar sizing, where both optimum designs are coincident. An analysis of the whole search space is included, and the optimization behaviour of evolutionary algorithms are compared with multiple population sizing and mutation rates in both problems. Results of average, best and standard deviation metrics indicate the success and the robustness of the methodology, as well as the fastest and easiest behaviour when considering the FSD case.

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Section: Introductionmentioning

confidence: 99%

Comparing the Fully Stressed Design and the Minimum Constrained Weight Solutions in Truss Structures

Computational Methods in Applied Sciences

Galván

et al. 2015

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“…In addition, they permit discrete optimization, matching real requirements in metallic bar structures. They have been applied in bar structures, trusses, and frames, as well as in metallic or concrete structures; surveys of the state of the art can be found in [2][3][4]. Their principal aim has been focused on the weight minimization problem, which is directly related with the raw material cost.…”

Section: Introductionmentioning

confidence: 99%

Engineering Knowledge-Based Variance-Reduction Simulation and G-Dominance for Structural Frame Robust Optimization

Advances in Mechanical Engineering

Galván

et al. 2013

This paper proposes the incorporation of engineering knowledge through both (a) advanced state-of-the-art preference handling decision-making tools integrated in multiobjective evolutionary algorithms and (b) engineering knowledge-based variancereduction simulation as enhancing tools for the robust optimum design of structural frames taking uncertainties into consideration in the design variables. The simultaneous minimization of the constrained weight (adding structural weight and average distribution of constraint violations) on the one hand and the standard deviation of the distribution of constraint violation on the other are handled with multiobjective optimization-based evolutionary computation in two different multiobjective algorithms. The optimum design values of the deterministic structural problem in question are proposed as a reference point (the aspiration level) in reference-point-based evolutionary multiobjective algorithms (here g-dominance is used). Results including -metric statistics in a structural frame test case with uncertain loads show considerable reductions in computational costs without harming the nondominated front quality, obtaining a design set that makes it possible to select minimum weight and maximum robustness optimum designs.

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A Diversity Dynamic Territory Nash Strategy in Evolutionary Algorithms: Enhancing Performances in Reconstruction Problems in Structural Engineering

Périaux

Computational Methods in Applied Sciences

et al. 2018