Improved particle swarm algorithm for interval nonlinear programming

This paper presents an improved particle swarm optimization for solving interval nonlinear programming, and considers the nonlinear programming problem, which is based on immune algorithm. And can make the particles only follow the global extremum and have a definite evolution direction when they are renewed. This improved approach has been tested on some problems commonly used in the literature. In all cases, our results show that the proposed approach is an efficient and can reach a higher precision.