Optimization of Plate girder using Genetic Algorithm by MATLAB

Abstract

In structural engineering the main goal of optimization lies in either one minimizing the weight of the structure or reducing its cost, keeping visible the overall safety and serviceability aspects. Engineering design is influenced by numerous parameters and associated constraints, therefore whereas designing a structure, various solutions are obtained, thereby creating it difficult to select an optimal solution. This study concerns with finding the geometric dimensions of the plate girder which minimize the total weight of plate girder and satisfy the design requirement using Genetic Algorithm (GA) and it is compared with different algorithms like Minimax optimization, Simulated Annealing Algorithm (SA) and Constrained Nonlinear minimization by Matrix Laboratory (MATLAB). A genetic algorithm (GA) is a technique for solving both constrained and unconstrained optimization problems based on a natural selection process that imitates biological evolution. The algorithm repeatedly modifies a population of individual solution and generates a population of points at each iteration. The design variables are taken as dimensions of plate girder. The total volume of a stiffened plate girder is minimized subject to the code provisions of IS800:2007. The paper presents the ability of genetic algorithms as a directed search method for optimum design of welded plate girder regulated by the mixed nature of design variables. The optimal design variables are found by using an algorithm and compared with conventional and different algorithms. The results are discussed.