Enhancing Particle Swarm Optimization with Gradient Information

Heuristic optimization provides a robust and efficient approach for solving complex real-world problems. This paper proposes an enhanced particle swarm optimization with gradient information (GPSO). Newton´s method is embedded in the velocity update equation to improve the effect of cognition influence. The performance of GPSO is tested using six benchmark multimodal functions and the numerical results comparison with other optimization methods demonstrate the effectiveness and efficiency of the proposed GPSO method.