An aggregate constraint method for non-linear programming

This paper presents a new and efficient method, referred to as an aggregate constraint method, for the solution of general non-linear programming problems in which a multi-constrained problem is converted to one with a single parametric constraint. This is derived by using the two concepts of constraint surrogation and maximum entropy, and represents a uniform approximation to the original constraint set. An augmented Lagrangean algorithm is then used to solve the resulting problem. Numerical examples are given to show the high efficiency of the present method.