2015
DOI: 10.1007/s00158-015-1339-4
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Multi-objective structural robust optimization under stress criteria based on mixed plate super-elements and genetic algorithms

Abstract: International audienceThis paper presents a methodology for the multi-objective (MO) robust optimization of plate structures under stress criteria, based on Mixed Super-Elements (MSEs). The optimization is performed with a classical Genetic Algorithm (GA) method based on Pareto-optimal solutions. It considers antagonist objectives among them stress criteria and thickness parameters distributed along the plate. This work aims at providing fast and efficient objective calculations. Our method is based on the imp… Show more

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Cited by 5 publications
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“…Genetic algorithm is a high parallel, random, and adaptive intelligent optimization algorithm [31]. An improved genetic algorithm can simulate stochastic and fuzzy characteristics in its process of producing population, crossover, and mutation operations and calculating value of chromosome [32].…”
Section: Improved Genetic Algorithm For Urban Drainage Systemmentioning
confidence: 99%
“…Genetic algorithm is a high parallel, random, and adaptive intelligent optimization algorithm [31]. An improved genetic algorithm can simulate stochastic and fuzzy characteristics in its process of producing population, crossover, and mutation operations and calculating value of chromosome [32].…”
Section: Improved Genetic Algorithm For Urban Drainage Systemmentioning
confidence: 99%