A New Hybrid Algorithm for Cost Optimization of Waffle Slab

Abstract In this paper, we have developed an efficient hybrid meta-heuristic algorithm for structural cost optimization of a waffle slab and have also solved the relevant optimization problems. The cost of the waffle slab is considered to be the objective function, and the design is based on the American Concrete Institute’s ACI 318-08 standard. This algorithm utilizes the recently developed mouth-brooding fish (MBF) algorithm as the main engine and uses the favorable properties of the colliding bodies optimization (CBO) algorithm. The performance of this algorithm is compared with MBF, CBO, harmony search (HS), particle swarm optimization (PSO), democratic particle swarm optimization (DPSO), charged system search (CSS) and enhanced charged system search (ECSS). The numerical results demonstrate that the proposed algorithm can construct promising results and has merits in solving challenging optimization problems.