An Efficient Hybrid Genetic Algorithm for Structural Form and Element Sizing Design Optimization of Tall Steel Frameworks

Topological optimization has been recognized as one of the most challenging and rewarding structural optimization task. For the past few decades, limited research on the simultaneous topological and sizing optimization of practical building structures has been carried out. In this paper, a novel hybrid optimization strategy, in which a local search operator developed based on a rigorously derived optimality criteria (OC) technique is embedded in the framework of genetic algorithm (GA), is proposed. The GA framework is particularly useful in the global exploration of optimal topologies, while the OC serves as a local search operator for an efficient refinement of the element sizes of given topologies. The hybridization strategy aims at striking a balance between the exploration of global search algorithms and the exploitation of efficient local search methods so as to able to solve for practical topological and element sizing optimization of tall steel building frameworks. The applicability and efficiency of the hybrid approach are illustrated through a 40-story planar frame example.

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