Generation of sustainable models with multi-objective optimum design of reinforced concrete (RC) structures

Abstract

Structural engineering has different designs, which are needed some requirements for generation suitable modelings. These requirements are related safety of structures and living creatures. Furthermore, some parameters are also evaluated like strength, sustainability, serviceability, etc. The second target should be handled through best modeling namely optimization. Thus, a bridge road can be constructed for cost efficiency or a steel system can be designed to provide the lightest weight. In this study, reinforced concrete beams were handled with rectangular and T-sections to provide carbon emission and total cost decrement. Optimal designs were generated towards different concrete strengths and analyzed for various reinforcement costs. Three metaheuristics were utilized: flower pollination algorithm, Jaya algorithm, harmony search. The best ones were determined about the single-objective application and utilized for multi-objective applications in minimization performance. It could be seen that optimal designs were created for several purposes such as economy, cleanliness, environment friendly, safety via cost, and CO2 emission minimization.