Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Bat algorithm for multi-objective optimisation
International Journal of Bio-Inspired Computation
Charged system search for optimal design of frame structures
Applied Soft Computing
An exponential big bang-big crunch algorithm for discrete design optimization of steel frames
Computers and Structures
A bat-inspired algorithm for structural optimization
Computers and Structures
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Bat inspired (BI) algorithm is a recently developed metaheuristic optimization technique inspired by echolocation behavior of bats. In this study, the BI algorithm is examined in the context of discrete size optimization of steel frames designed for minimum weight. In the optimum design problem frame members are selected from available set of steel sections for producing practically acceptable designs subject to strength and displacement provisions of American Institute of Steel Construction-Allowable Stress Design (AISC-ASD) specification. The performance of the technique is quantified using three real-size large steel frames under actual load and design considerations. The results obtained provide a sufficient evidence for successful performance of the BI algorithm in comparison to other metaheuristics employed in structural optimization.