#structural optimization

This paper presents Reinforced Concrete RC slab design optimization technique for finding the best design parameters that satisfy the project requirements both in terms of strength and serviceability criteria while keeping the overall construction cost to a minimum. In this paper four different types of RC slab design named as simply supported slab, one end continuous slab, both end continuous slab and cantilever slab are optimized using three different metaheuristic optimization algorithms named as Genetic Algorithms GA , Particle Swarm Optimization PSO and Gray Wolf Optimization GWO . The slabs with various end conditions are formulated according to the ACI code. The formulated problem contains three optimization variables, the thickness of the slab, steel bar diameter, and bar spacing while objective involves the minimization of overall cost of the structure which includes the cost of concrete, cost of reinforcement and the constraints involves the design requirement and ACI codes limit. The proposed method is developed using MATLAB. Finally, to validate the performance of the proposed algorithm the results are compared with the previously proposed algorithms. The comparison of results shows that the proposed method provides a significant improvement over the previously proposed algorithms.