A comparative approach for the optimal design of steel structures using biogeography-based optimization (BBO) algorithm and genetic algorithm (GA)

Abstract

Structural optimization is one of the key concerns of civil engineering designers, but from a mathematical point of view, this optimization problem is highly complex and complicated due to a large number of non-linear design constraints and the iterative procedure of structural analysis. Introducing optimization algorithms such as biogeography-Based Optimization (BBO) and genetic algorithms (GA) into applications can help the user to optimize the cost of the structure to be adopted more quickly and with fewer errors in the preliminary phase of the design study. The aim of this research is to carry out a comparative approach to structure weight minimization using biogeography-Based Optimization (BBO) algorithm and genetic algorithms (GA), examining the influence of the number of populations and the number of iterations in the final results. In this study, both algorithms gave reliable results, but a comparison of the results obtained by the two methods reveals that the biogeography-Based Optimization algorithm (BBO) can be successfully used for the optimization of steel structures while ensuring verification of the strength, serviceability and stability criteria defined by Eurocode 3 (Union, 2006), as it has certain advantages in detecting the global minimum over genetic algorithms (GA). It is capable of finding solutions that are lighter, stiffer and have lower deflection than the original designs.