The long-step method is an approach used in path-following algorithms for nonlinear optimization that focuses on taking larger steps along the central path towards an optimal solution. This technique is designed to improve convergence rates by navigating efficiently through feasible regions of the solution space, ensuring that the method remains within bounds while maximizing progress towards the goal.
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