The performance of linear solvers is very dependent on their parameters and finding an optimal setting for parameters is a challenge. In this paper we propose a setting for CPLEX parameters to reduce the solving time of linear models. Our experimental results show that our setting is more efficient than the solver default setting
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
This paper is concerned with an optimal expansion of linear discrete time systems on Meixner functio...
With the increasing sophistication in the use of optimization algorithms such as deep learning on em...
This paper is a concise guide to CPLEX, the leading solver for linear and convex quadratic optimisat...
Mixed integer programming (MIP) problems are highly parameterized, and finding parameter settings th...
It is well-known that the efficiency of mixed integer linear mathematical programming depends on the...
Mathematical solvers can be parameterized today with a multitude of different parameters. While defa...
This paper addresses the problem of tuning parameters of mathematical solvers to increase their perf...
An extension of the Nelder-Mead simplex algorithm is presented in this dissertation. The algorithm ...
Usually, in data processing, to find the parameters of the models that best fits the data, people us...
One of the key difficulties in Constraint Modeling lies in for- mulating an effective constraint mod...
In his recent work, Dadush et al. introduced the condition number κ for constraint matrices of linea...
Solving a linear system $Ax=b$ is a fundamental scientific computing primitive for which numerous so...
Cette thèse vise à concevoir des solveurs efficaces pour résoudre des systèmes linéaires, résultant ...
International audienceWe discuss the issue of finding a good mathematical programming solver configu...
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
This paper is concerned with an optimal expansion of linear discrete time systems on Meixner functio...
With the increasing sophistication in the use of optimization algorithms such as deep learning on em...
This paper is a concise guide to CPLEX, the leading solver for linear and convex quadratic optimisat...
Mixed integer programming (MIP) problems are highly parameterized, and finding parameter settings th...
It is well-known that the efficiency of mixed integer linear mathematical programming depends on the...
Mathematical solvers can be parameterized today with a multitude of different parameters. While defa...
This paper addresses the problem of tuning parameters of mathematical solvers to increase their perf...
An extension of the Nelder-Mead simplex algorithm is presented in this dissertation. The algorithm ...
Usually, in data processing, to find the parameters of the models that best fits the data, people us...
One of the key difficulties in Constraint Modeling lies in for- mulating an effective constraint mod...
In his recent work, Dadush et al. introduced the condition number κ for constraint matrices of linea...
Solving a linear system $Ax=b$ is a fundamental scientific computing primitive for which numerous so...
Cette thèse vise à concevoir des solveurs efficaces pour résoudre des systèmes linéaires, résultant ...
International audienceWe discuss the issue of finding a good mathematical programming solver configu...
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
This paper is concerned with an optimal expansion of linear discrete time systems on Meixner functio...
With the increasing sophistication in the use of optimization algorithms such as deep learning on em...