A comparison of simulated annealing and genetic algorithm for optimum design of nonlinear steel space frames

A comparison of simulated annealing and genetic algorithm for optimum design of nonlinear steel space frames

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Article ID: iaor20083188
Country: Germany
Volume: 34
Issue: 4
Start Page Number: 347
End Page Number: 359
Publication Date: Oct 2007
Journal: Structural and Multidisciplinary Optimization
Authors:
Keywords: heuristics: local search, heuristics: genetic algorithms
Abstract:

In this article, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames that are based on simulated annealing and genetic algorithm. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as the American Institute of Steel Construction (AISC) wide-flange shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) and AISC Allowable Stress Design (ASD) specifications, maximum (lateral displacement) and interstorey drift constraints, and also size constraints for columns were imposed on frames. The algorithms were applied to the optimum design of three space frame structures, which have a very small amount of nonlinearity. The unconstrained form of objective function was applied in both optimum design algorithms, and constant penalty factors were used instead of gradually increasing ones. Although genetic algorithm took much less time to converge, the comparisons showed that the simulated annealing algorithm yielded better designs together with AISC-LRFD code specification.

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