Weighted Gradient Direction Based Chaos Optimization Algorithm for Nonlinear Programming Problem

摘要

Based on exact penalty function, a chaos optimization algorithm using weighted gradient direction search is proposed for handling nonlinear programming problems with inequality constraints. By use of ergodicity and intrinsic stochastic properties of chaos, the chaos optimization algorithm can escape from the local minima. Solution acceleration method using weighted gradient direction search is implemented which improve the chaos optimization algorithm, so as to speed up the rate of convergence and improve the accuracy of solution. A comparison is carried out with other chaos algorithms, and numerical results illustrate the well convergence and high search speed of the proposed algorithm.