El-Cezeri Journal of Science and Engineering, vol.9, no.1, pp.49-64, 2022 (Scopus)
Optimization has become the most important subject of engineering designs as a result of developed information technologies. Determining optimal values among a large number of alternatives that provide design terms and conditions is also an important problem for Structural Engineering. In the design of two-way slabs, there are many alternatives that will meet the limit state criteria of TS500 without exceeding the deflection limits of the slab. Among these alternatives, it is necessary to choose the most useful and economical one. If a criterion for optimal design is put forward, this will be an important guide for the designer. The particle swarm optimization (PSO) algorithm, which occupies an important place among metaheuristic optimization techniques, is one of the population-based search algorithms and its use is quite common. As part of this study, the particle swarm algorithm was used. In this study, the PSO algorithm has been modified to perform reliability-based discrete optimization and the optimization of slabs with two-direction changing dimensions has been performed. In the optimization, TS500 conditions, limit state and displacement criteria are defined as constraints. For this purpose, models were created for different slab types with increasing short edge (2.2-8.6 m) and changing m (Llong/Lshort) values. The section and reinforcement to be selected are optimized by reliability-based discrete (discontinuous) optimization analysis. A total of 5236 models were analyzed in the study. Optimal design values for different slabs are determined as a result of the analysis.