Solving second-order conic systems with variable precision
arXiv:1104.13521 citationsh-index: 36
Originality Synthesis-oriented
AI Analysis
It addresses the practical implementation of conic feasibility solvers with limited precision, which is relevant for real-world computing environments.
The paper presents an interior-point method for deciding feasibility of second-order conic systems using finite-precision arithmetic, providing bounds on the number of operations and required precision.
We describe and analyze an interior-point method to decide feasibility problems of second-order conic systems. A main feature of our algorithm is that arithmetic operations are performed with finite precision. Bounds for both the number of arithmetic operations and the finest precision required are exhibited.