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Paper Count: 30517
Elitist Self-Adaptive Step-Size Search in Optimum Sizing of Steel Structures
This paper covers application of an elitist selfadaptive
step-size search (ESASS) to optimum design of steel
skeletal structures. In the ESASS two approaches are considered for
improving the convergence accuracy as well as the computational
efficiency of the original technique namely the so called selfadaptive
step-size search (SASS). Firstly, an additional randomness
is incorporated into the sampling step of the technique to preserve
exploration capability of the algorithm during the optimization.
Moreover, an adaptive sampling scheme is introduced to improve the
quality of final solutions. Secondly, computational efficiency of the
technique is accelerated via avoiding unnecessary analyses during the
optimization process using an upper bound strategy. The numerical
results demonstrate the usefulness of the ESASS in the sizing
optimization problems of steel truss and frame structures.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339117Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1017
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