โ Scribed by Marius Sinclair
No coin nor oath required. For personal study only.
Nonlinear integer programming problems with bounded feasible sets are considered. It is shown how the number of constraints in such problems can be reduced with the aid of an exact penalty function approach. This approach can be used to construct an equivalent unconstrained problem, or a problem with a constraint set which makes it easier to solve. The application of this approach to various nonlinear integer programming problems is discussed.
๐ SIMILAR VOLUMES
In this paper, we propose a novel objective penalty function for inequality constrained optimization problems. The objective penalty function differs from any existing penalty function and also has two desired features: exactness and smoothness if the constraints and objective function are different
Motivated by the recent developments of the Control Parametrization Enhancing Technique (CPET), a novel method for solving a general cleee of nonlinear mixed integer prcgramming problems is introduced in thii paper. By imposing appropriate dynamice as well ee a set of statistical variance type of fu