Modified Particle Swarm Optimization Algorithm for Engineering Structural Optimization Problem

This paper introduces a modified particle swarm optimization algorithm (MPSO) to solve the engineering structural optimization problems. In order to balance the objective function value and constraint violation of particles, we present an improved adaptive fitness method. The teaching mechanism is used to guide the population evolution in feasible region, and the algorithm uses the adaptive inertial weight and learning factors to balance exploration and exploitation. Finally, the particle reset strategy can avoid the algorithm into local optimum effectively. The algorithm was validated using two benchmark engineering optimization problems. Comparison of obtained computation results with other existing optimization methods shows the superiority of the MPSO in terms of accuracy.