Optimization of Rcc Dome using Genetic Algorithm

Abstract

Optimization is the selection of a best element (with regard to some criteria) from some set of available alternatives. More generally, optimization includes finding "best available" values of some objective function given a defined domain, including a variety of different types of objective functions and different types of domains. The best design of a structure means the most economic structure without impairing the functional purposes the structure is supposed to serve.

Genetic Algorithms (GA) belongs to the family of evolutionary algorithms. GA is an iterative procedure that is motivated by the "survival of the fittest” principle of Darwinian theory of natural solutions.

 In the present work, optimum design of reinforced concrete spherical dome is studied according to IS 456-2000. The objective function is the total cost of the concrete dome which includes the costs of concrete and steel excluding formwork. In the proposed optimization, the cross sectional dimensions of dome along with the number of bars and diameter of the reinforcement bars are considered as design variables. The design constraints are sizing, allowable compressive strength of concrete and buckling. The MATLAB Programming code has been developed for the analysis of 2D Reinforced Concrete dome and for Genetic Algorithm process. The concept and working of GA methodology has been studied and appropriate codes have been formulated. The GA program has been developed to deal with continuous as well as discrete variables. The results are studied for the optimum cost of dome for number of generations and number of population sizes. It shows that the number of iterations of 250 and the population size of 30 give the best solution. Thus, it is concluded that as the number of generations and population size increases, the obtained solution enhances up to a certain limit, beyond which the solution will no longer enhance.