CO2 emission optimization of composite floor systems with cellular beams via metaheuristics algorithms

In this study, the optimization of the composite floor system with cellular beams is investigated. The objective function is the minimization of carbon dioxide (CO2) emissions and the optimal solution is defined by 19 design variables for the beam's topology, beams fabricated process, steel deck characteristics, columns. The requirements of the ultimate and serviceability state limits are considered for the composite floor system design. The program is developed within the MATLAB platform. A number of the benchmark test problems of composite floor systems with full web beams are optimized with cellular beams to verify the reduction of total CO2 emission. The optimum results are obtained by Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Bonobo Algorithm (BO). A comparison of the performance of these algorithms shows that the BO algorithm has a higher search capability and results in better solutions than PSO and GA algorithms in the optimization of the composite floor system with the cellular beams and the use of cellular beams can reduce the total CO2 emissions of the floor above 20%.