Structural design optimization (SDO) has long promised to revolutionize structural design, yet its impact on everyday engineering remains limited. This review synthesizes 25 years of research on SDO of concrete slabs in buildings. Increasingly volatile and conflicting objectives, and the rise of non-standard, material-efficient slab systems, challenge established design methods. SDO can address such problems by formulating them as mathematical optimization problems (OPs). Following PRISMA 2020, we identified 63 relevant publications from 906 records, comprising 151 OPs across eight slab types. We analyze OP formulations, analysis and optimization methods, and design insights. Flat, solid, and ribbed slabs account for more than 85% of OPs, while non-standard slab systems remain rare. OP complexity ranges from 1 to > 100,000 variables and 0–49 constraints, yet no recurring formulation defines a standard OP for any slab type. Metaheuristics dominate algorithm choice, although cross-class benchmarks provide limited support for this dominance. Many studies provide design insights, only 10% address real projects, and no optimized design is reported as built or issued for construction. Heterogeneous OP formulations, inconsistent reporting, weak baselines, and insufficient cross-class algorithm benchmarking hinder comparability and prevent study-specific insights from becoming transferable design guidance. Key research gaps include representative cross-class benchmarking suites, further work on analysis and solution-mapping surrogates, expanded case studies on non-standard slab systems, and multi-objective optimization under objective-input uncertainty.
Dombrowski et al. (Fri,) studied this question.