Optimum Cost Design of Reinforced Concrete Slabs Using Mouth Brooding Fish Algorithm

In this article, the optimum design of a reinforced concrete solid slab is presented via the Mouth Brooding Fish (MBF) algorithm that is recently developed. It is based on mouth brooding fish life cycle. This algorithm utilizes the movements of the mouth brooding fish and their children’s struggle for survival as a pattern to find the best possible answer. The cost of the solid slab is considered to be the objective function, and the design is based on the ACI code. The efficiency of this algorithm is compared with Neural Dynamic (ND) and Particle Swarm Optimization (PSO). The numerical results indicate that the MBF algorithm can to construct very promising results and has merits in solving challenging optimization problems.