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pro vyhledávání: '"Ambròs A"'
For almost two decades, mixed integer programming (MIP) solvers have used graph-based conflict analysis to learn from local infeasibilities during branch-and-bound search. In this paper, we improve MIP conflict analysis by instead using reasoning bas
Externí odkaz:
http://arxiv.org/abs/2410.15110
This note proposes semi-parametric tests for investigating whether a stochastic process is fractionally integrated of order $\delta$, where $|\delta| < 1/2$, when smooth trends are present in the model. We combine the semi-parametric approach by Iaco
Externí odkaz:
http://arxiv.org/abs/2410.10749
The recent performance improvements in mixed-integer programming (MIP) went along with a significantly increased complexity of the codes of MIP solvers, which poses challenges in fixing implementation errors. In this paper, we introduce MIP-DD, a sol
Externí odkaz:
http://arxiv.org/abs/2405.19770
Semi-continuous decision variables arise naturally in many real-world applications. They are defined to take either value zero or any value within a specified range, and occur mainly to prevent small nonzero values in the solution. One particular cha
Externí odkaz:
http://arxiv.org/abs/2403.19411
This paper presents the integration of constraint propagation and dual proof analysis in an exact, roundoff-error-free MIP solver. The authors employ safe rounding methods to ensure that all results remain provably correct, while sacrificing as littl
Externí odkaz:
http://arxiv.org/abs/2403.13567
Autor:
Bolusani, Suresh, Besançon, Mathieu, Bestuzheva, Ksenia, Chmiela, Antonia, Dionísio, João, Donkiewicz, Tim, van Doornmalen, Jasper, Eifler, Leon, Ghannam, Mohammed, Gleixner, Ambros, Graczyk, Christoph, Halbig, Katrin, Hedtke, Ivo, Hoen, Alexander, Hojny, Christopher, van der Hulst, Rolf, Kamp, Dominik, Koch, Thorsten, Kofler, Kevin, Lentz, Jurgen, Manns, Julian, Mexi, Gioni, Mühmer, Erik, Pfetsch, Marc E., Schlösser, Franziska, Serrano, Felipe, Shinano, Yuji, Turner, Mark, Vigerske, Stefan, Weninger, Dieter, Xu, Liding
The SCIP Optimization Suite provides a collection of software packages for mathematical optimization, centered around the constraint integer programming (CIP) framework SCIP. This report discusses the enhancements and extensions included in the SCIP
Externí odkaz:
http://arxiv.org/abs/2402.17702
The length-constrained cycle partition problem (LCCP) is a graph optimization problem in which a set of nodes must be partitioned into a minimum number of cycles. Every node is associated with a critical time and the length of every cycle must not ex
Externí odkaz:
http://arxiv.org/abs/2401.17937
It is well known that reformulating the original problem can be crucial for the performance of mixed-integer programming (MIP) solvers. To ensure correctness, all transformations must preserve the fea sibility status and optimal value of the problem,
Externí odkaz:
http://arxiv.org/abs/2401.09277
This article studies a combination of the two state-of-the-art algorithms for the exact solution of linear programs (LPs) over the rational numbers, i.e., without any roundoff errors or numerical tolerances. By integrating the method of precision boo
Externí odkaz:
http://arxiv.org/abs/2311.08037
We present a proof system for establishing the correctness of results produced by optimization algorithms, with a focus on mixed-integer programming (MIP). Our system generalizes the seminal work of Bogaerts, Gocht, McCreesh, and Nordstr\"om (2022) f
Externí odkaz:
http://arxiv.org/abs/2311.03877