Abstract
Many of the theoretical results of the previous chapters about interior-point methods for solving linear programs also hold for nonlinear convex programs. In this chapter we intend to give a simple self-contained introduction to primal methods for convex programs. Our focus is on the theoretical properties of the methods; in Section 7.3, we try to bridge the gap between theory and implementation, and propose a primal long-step predictor-corrector infeasible interior-point method for convex programming. Our presentation follows the outline in [19]; for a comprehensive treatment of interior-point methods for convex programs we refer to [29] or [7]
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Jarre, F. (1996). Interior-Point Methods for Classes of Convex Programs. In: Terlaky, T. (eds) Interior Point Methods of Mathematical Programming. Applied Optimization, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3449-1_7
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DOI: https://doi.org/10.1007/978-1-4613-3449-1_7
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