Computational Strategy for Structural Analysis, Design, and Optimization of Trusses Using Genetic Algorithm and Particle Swarm Optimization

Integrated structural analysis and design software packages, which generally work on finite element method for analysis and design, have been gaining popularity in the field of designing since they have reduced the tedious calculation process to a simple process of just giving input values. The result generated is according to the values entered without the consideration of the feasibility. Moreover, optimization of structures has been a lesser used concept in day-to-day working and is independent of design and analysis of the structures. In this paper, an attempt has been made to integrate analysis and design along with optimization for a 3-bar truss. The objective functions for optimization are weight minimization and minimization of vertical displacement. The design and analysis components are included as constraints of the objective function to be optimized. Optimization is performed by two different methods: Genetic Algorithm and Particle Swarm Optimization. This is done to compare which of the algorithms gives better results and is less time consuming. The objective functions, that are weight and vertical displacement, are evaluated individually as single objective functions and combined as multi-objective functions. Pareto-optimal method is used to get a non-dominated set in multi-objective optimization. The inputs given are range of the area of the bar and number of generations. Also, the comparisons of results are of Particle Swarm Optimization and Genetic Algorithm is done.