Object Library of Algorithms for Dynamic Optimization Problems: Benchmarking SQP and Nonlinear Interior Point Methods

Object Library of Algorithms for Dynamic Optimization Problems: Benchmarking SQP and Nonlinear Interior Point Methods

The main purpose of this paper is to describe the design, implementation and possibilities of our object-oriented library of algorithms for dynamic optimization problems. We briefly present library classes for the formulation and manipulation of dynamic optimization problems, and give a general survey of solver classes for unconstrained and constrained optimization. We also demonstrate methods ...

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...

Interior Point Methods for Nonlinear Optimization

Interior-point methods for optimization

This article describes the current state of the art of interior-point methods (IPMs) for convex, conic, and general nonlinear optimization. We discuss the theory, outline the algorithms, and comment on the applicability of this class of methods, which have revolutionized the field over the last twenty years.

Two Interior-point Methods for Nonlinear P ( )-complementarity Problems

1 The authors would like to thank two anonymous referees for their helpful suggestions leading to a improved presentation of the paper. Abstract. Two interior-point algorithms using a wide neighborhood of the central path are proposed to solve nonlinear P-complementarity problems. The proof of the polynomial complexity of the rst method requires that the problem satisses a scaled Lipschitz cond...