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

Abstract

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.

Optimal design of elastic and elastoplastic tuned mass dampers using the Mouth Brooding Fish algorithm for linear and nonlinear structures

“…This algorithm mimics the movements of the Cichlid family as a foundation to solve optimization problems. Considering the effects of various factors on the movements of this fish family, including the main movements of each fish, the movements of left-out fish, shark attacks, or various dangers, and integrating the roulette wheel selection, the algorithm seeks to find the optimal solution for a selected problem [44].…”