Linearly Constrained Augmented Lagrangian: MINOS

Neculai Andrei
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Neculai Andrei: Center for Advanced Modeling & Optimization

Chapter Chapter 9 in Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology, 2017, pp 223-241 from Springer

Abstract: Abstract In this chapter we present one of the most respectable algorithms and softwares for solving general nonlinear optimization problems given by Murtagh and Saunders (1978, 1980, 1982, 1995). The main idea behind this method is to generate a step by minimizing the Lagrangian or the augmented Lagrangian subject to the linearizations of the constraints.

Date: 2017
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DOI: 10.1007/978-3-319-58356-3_9

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