Solving Semi-Infinite Optimization Problems with Interior Point Techniques

Solving Semi-Infinite Optimization Problems with Interior Point Techniques

We introduce a new numerical solution method for semi-infinite optimization problems with convex lower level problems. The method is based on a reformulation of the semi-infinite problem as a Stackelberg game and the use of regularized nonlinear complementarity problem functions. This approach leads to central path conditions for the lower level problems, where for a given path parameter a smoo...

Solving Disjunctive Optimization Problems by Generalized Semi-infinite Optimization Techniques

We describe a new possibility to model disjunctive optimization problems as generalized semi-infinite programs. In contrast to existing methods, for our approach neither a conjunctive nor a disjunctive normal form is expected. Applying existing lower level reformulations for the corresponding semi-infinite program we derive conjunctive nonlinear problems without any logical expressions, which c...

Proximal Interior Point Approach for Solving Convex Semi-infinite Programming Problems

1 A regularized logarithmic barrier method for solving ill-posed convex semi-infinite programming problems is considered. In this method a multistep proximal regularization is coupled with an adaptive discretization strategy in the framework of the interior point approach. Termination of the proximal iterations at each discretization level is controlled by means of estimates, characterizing the...

Interior-point algorithms for semi-infinite programming

Novel Interior Point Algorithms for Solving Nonlinear Convex Optimization Problems

This paper proposes three numerical algorithms based on Karmarkar’s interior point technique for solving nonlinear convex programming problems subject to linear constraints. The first algorithm uses the Karmarkar idea and linearization of the objective function.The second and third algorithms are modification of the first algorithm using the Schrijver andMalek-Naseri approaches, respectively. T...