Multi-Variable Multi-Objective Optimization Analysis of Super-Tall Building Structures Based on a Genetic Algorithm

Balancing structural safety and economic efficiency in super-tall building design remains a formidable challenge. To address this issue, this study proposes a genetic-algorithm-based multi-variable, multi-objective optimization method. The design variables include the member sizes and vertical layout positions of outrigger and belt trusses, as well as the cross-sectional dimensions of mega-columns. Total structural weight and maximum inter-story drift ratio are adopted as objective functions, while code-specified constraints, such as shear-weight ratio, stiffness-weight ratio, and axial compression ratio, are incorporated to formulate the fitness evaluation for optimization. Taking a 300 m baseline structure designed for 6-degree seismic intensity and equipped with two outrigger trusses and three belt trusses as an example, single-variable sensitivity analyses are first performed. The results show that optimizing any single parameter can yield certain local improvements, yet it cannot overcome the weight–deformation trade-off induced by strong variable coupling. By selecting representative feasible solutions from the multi-variable solution set that match the “optimal” values identified by single-variable optimization as benchmarks, the multi-variable optimum reduces the total structural weight by approximately 6.5–18.4% relative to these representative designs. Moreover, optimal layout strategies of outrigger and belt trusses are investigated for two typical building heights (200 m and 300 m) and two seismic intensity levels associated with design ground motions having a 10% exceedance probability in 50 years, namely 6-degree (0.05 g) and 8-degree (0.20 g). Finally, the proposed method is validated through a case study of a super-tall financial center in Chongqing, where the total structural weight is reduced by 12.3% after optimization while the inter-story drift ratio still satisfies relevant code requirements. The results demonstrate that the proposed framework can generate competitive feasible solutions and provide a systematic means to achieve a balanced trade-off between structural safety and economic efficiency for outrigger–belt-truss super-tall buildings.