Design and implementation of a modular interior-point solver for linear optimization
نویسندگان
چکیده
This paper introduces the algorithmic design and implementation of Tulip, an open-source interior-point solver for linear optimization. It implements a regularized homogeneous algorithm with multiple centrality corrections, therefore handles unbounded infeasible problems. The is written in Julia, thus allowing flexible efficient implementation: Tulip's framework fully disentangled from algebra implementations model's arithmetic. In particular, this allows to seamlessly integrate specialized routines structured Extensive computational results are reported. We find that Tulip competitive solvers on H. Mittelmann's benchmark barrier programming solvers. Furthermore, we master problems context Dantzig-Wolfe decomposition. These yield tenfold speedup large dense instances arise power systems operation two-stage stochastic programming, thereby outperforming state-of-the-art commercial interior point method Finally, illustrate ability use different levels arithmetic precision by solving extended precision.
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ژورنال
عنوان ژورنال: Mathematical Programming Computation
سال: 2021
ISSN: ['1867-2957', '1867-2949']
DOI: https://doi.org/10.1007/s12532-020-00200-8