Kernel function-based interior-point algorithms for linear optimisation

Citation:

Bounibane B, Djeffal E-A. Kernel function-based interior-point algorithms for linear optimisation. International Journal of Mathematical Modelling and Numerical Optimisation [Internet]. 2019;9 (2) :158.

Abstract:

We propose a primal-dual interior-point algorithm for linear optimisation based on a class of kernel functions which is eligible. New search directions and proximity measures are defined based on these functions. We derive the complexity bounds for large and small-update methods respectively. These are currently the best known complexity results for such methods.

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