A PSO Algorithm Based on Orthogonal Test Design

We present a particle swarm optimization algorithm OT-PSO using orthogonal test technique. Based on the classical PSO, OT-PSO searches for local optimum in the neighbor area of the global best solution by using the method of orthogonal test design. OT-PSO can probe the solutions uniformly distributed in the search space and select the better ones. Using those better solutions OT-PSO can guide the particles searching towards the correct direction in the latter iterations so as to speed up the convergence, get more precise solutions and avoid local optimum. Our experimental results show that OT-PSO algorithm not only has faster convergence speed, but also can improve the accuracy of solutions effectively and enhance the robustness of the algorithm.