@article {6874,
	title = {Kernel function-based interior-point algorithms for linear optimisation},
	journal = {International Journal of Mathematical Modelling and Numerical Optimisation },
	volume = {9},
	number = {2},
	year = {2019},
	pages = {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.

},
	url = {https://www.inderscienceonline.com/doi/abs/10.1504/IJMMNO.2019.098785},
	author = {Bounibane, Bachir and Djeffal, El-Amir}
}
