Particle Swarm Optimization for Structural Design Problems

The aim of this paper is to employ the particle swarm optimization (pso) technique to a mechanical engineering design problem which is minimizing the volume of a cantilevered beam subject to bending strength constraints. mechanical engineering design problems are complex activities which are computing capability are more and more required. the most of these problems are solved by conventional mathematical programming techniques that require gradient information. these techniques have several drawbacks from which the main one is becoming trapped in local optima. as an alternative to gradient-based techniques, the pso does not require the evaluation of gradients of the objective function. the pso algorithm employs the generation of guided random positions when they search for the global optimum point. the pso which is a nature inspired heuristics search technique imitates the social behavior of bird flocking. the results obtained by the pso are compared with mathematical programming (mp). it is demonstrated that the pso performed and obtained better convergence reliability on the global optimum point than the mp. using the mp, the volume of 2961000 mm3 was obtained while the beam volume of 2945345 mm3 was obtained by the pso.