Optimal test selection of complex electronic systems based on improved discrete particle swarm optimization algorithm

Optimal test selection is the important content of complex electronic system testability design. This chapter establishes the mathematical model of optimal test selection and then proposes an improved discrete particle swarm optimization algorithm to provide a solution. The algorithm designs a new fitness function according to the characteristics of test selection. In order to avoid the local optimum, an inertia weight adaptive adjustment strategy based on the group’s premature degree is proposed. The simulation results show that the algorithm proposed can achieve a global optimal solution fast and effectively. Optimization results meet all system requirements and can provide an effective guidance for optimal test selection of complex electronic systems. © Springer International Publishing Switzerland 2015.