An improved particle swarm optimization for economic dispatch problems with non-smooth cost functions

This paper presents a novel and efficient method for solving the economic dispatch problems with non-smooth cost functions, by integrating the particle swarm optimization (PSO) with the chaotic sequences. The proposed improved particle swarm optimization (IPSO) combines the particle swarm optimization algorithm with chaotic sequences technique. A particle swarm optimization is one of the most powerful methods for solving global optimization problems. The application of chaotic sequences in PSO is an efficient strategy to improve the global searching capability and escape from local minima. To show the effectiveness of the proposed method, the numerical studies have been performed for three different sample systems. The proposed IPSO outperforms other state-of-the-art algorithms in solving economic dispatch problems with valve-point and multi-fuel effects.