Study on the strategy of decreasing inertia weight in particle swarm optimization algorithm

To efficiently control the global and local search of particle swarm optimization (PSO), motivated by the idea of decreasing inertia weight (DIW), three nonlinear strategies for DIW, a parabola opening upwards, a parabola opening downwards and an exponential curve, are proposed based on the existing linear DIW. Sphere, Rosenbrock, Griewank and Rastrigrin functions are used to evaluate the strategies on the PSO performance. The experimental results show that for most continuous optimization problems, the strategy of concave function gains an advantage over the linear strategy, while the linear strategy outperforms strategy of convex function with the identical initial and final weights.