EXACT PENALTY FUNCTION ALGORITHM FOR SOLVING GENERAL CONSTRAINED PARAMETER OPTIMIZATION PROBLEMS

An exact penalty function type of algorithm is proposed to solve a general class of constrained parameter optimization problems. The proposed algorithm has the property that any solution obtained by it will always satisfy the problem constraints, and that it will obtain a solution to the constrained problem, within a given specified tolerance, by solving a single unconstrained problem, i.e. it is not necessary to solve a sequence of unconstrained optimization problems. The algorithm applies a modification of Rosenbrock's (Rosenbrock, 1960) polynomial boundary penalty function, and a negative exponential penalty function with moving parameters, to modify the objective function in the neighborhood of the constrained region; a robust unconstrained algorithm (Davison and Wong, 1975) is then used to solve the resulting unconstrained optimization problem. Some standard test functions are included to show the performance of the algorithhm. Application of the algorithm is then made to solve some computer-aided design problems occurring in the area of control system synthesis. © 1979.