AN ALL-PURPOSE EVOLUTIONARY ALGORITHM FOR SOLVING NONLINEAR PROGRAMMING PROBLEMS

A new evolutionary algorithm for solving the nonlinear programming （NLP） problems is proposed in this paper. It’s based on Guo’s algorithm and has added some capabilities for solving NLP problems, such as introdusing the variable subspace, adding a search process of subspace and normalized constraints, and adding the function to deal with the equality constraints, integer NLP problems, 0-1 NLP problems and mixed-integer NLP problems that make it a really all-purpose algorithm for solving nonlinear programming problems. Numerical experiments show that the new algorithm is not only an all-purpose algorithm, but also a high-performance algorithm with better results than others.