Abstract. Current mixed-integer linear programming solvers are based on linear programming routines that use °oating-point arithmetic. Occasionally, this leads to wrong solutions, even for problems where all coe±cients and all solution components are small integers. An example is given where many state-of-the-art MILP solvers fail. It is then shown how, using directed rounding and interval arithmetic, cheap pre- and postprocessing of the linear programs arising in a branch-and-cut framework can guarantee that no solution is lost, at least for mixed-integer programs in which all variables can be bounded rigorously by bounds of reasonable size
One of the most important breakthroughs in the area of Mixed Integer Linear Programming (MILP) is th...
[[abstract]]Several algorithms have been developed to solve the two-level linear programming problem...
Solving (mixed) integer (linear) programs, (M)I(L)Ps for short, is a fundamental optimisation task w...
Mixed-integer programs (MIPs) involving logical implications modeled through big-M coefficients are ...
In this work we focus on various cutting-plane methods for Mixed-integer Linear Programming (MILP) p...
This tutorial presents a theory of valid inequalities for mixed integer linear sets. It introduces t...
We consider feasibility of linear integer programs in the context of verification systems such as SM...
We consider a class of linear programs involving a set of covering constraints of which at most k ar...
Abstract. A wide variety of problems in global optimization, combinatorial optimization as well as s...
Real world mixed integer linear programming (MILP) models often contain numeric and hence uncertain ...
My work focuses on cutting planes technology in Mixed Integer Programming. I explore novel classes o...
We consider a class of linear programs involving a set of covering constraints of which at most k ar...
Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Resear...
Algorithms and computer-based tools for analyzing infeasible linear and nonlinear programs have been...
Mixed integer programming (MIP) is commonly used to model indicator constraints, i.e., constraints t...
One of the most important breakthroughs in the area of Mixed Integer Linear Programming (MILP) is th...
[[abstract]]Several algorithms have been developed to solve the two-level linear programming problem...
Solving (mixed) integer (linear) programs, (M)I(L)Ps for short, is a fundamental optimisation task w...
Mixed-integer programs (MIPs) involving logical implications modeled through big-M coefficients are ...
In this work we focus on various cutting-plane methods for Mixed-integer Linear Programming (MILP) p...
This tutorial presents a theory of valid inequalities for mixed integer linear sets. It introduces t...
We consider feasibility of linear integer programs in the context of verification systems such as SM...
We consider a class of linear programs involving a set of covering constraints of which at most k ar...
Abstract. A wide variety of problems in global optimization, combinatorial optimization as well as s...
Real world mixed integer linear programming (MILP) models often contain numeric and hence uncertain ...
My work focuses on cutting planes technology in Mixed Integer Programming. I explore novel classes o...
We consider a class of linear programs involving a set of covering constraints of which at most k ar...
Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Resear...
Algorithms and computer-based tools for analyzing infeasible linear and nonlinear programs have been...
Mixed integer programming (MIP) is commonly used to model indicator constraints, i.e., constraints t...
One of the most important breakthroughs in the area of Mixed Integer Linear Programming (MILP) is th...
[[abstract]]Several algorithms have been developed to solve the two-level linear programming problem...
Solving (mixed) integer (linear) programs, (M)I(L)Ps for short, is a fundamental optimisation task w...