\u3cp\u3eThis paper considers integer formulations of binary sets X of minimum sparsity, i.e., the maximal number of non-zeros for each row of the corresponding constraint matrix is minimized. Providing a constructive mechanism for computing the minimum sparsity, we derive sparsest integer formulations of several combinatorial problems, including the traveling salesman problem. We also show that sparsest formulations are NP-hard to separate, while (under mild assumptions) there exists a dense formulation of X separable in polynomial time.\u3c/p\u3
We present a dual-scaling interior-point algorithm and show how it exploits the structure and sparsi...
We show how to efficiently model binary constraint problems (BCP) as integer programs. After conside...
An intensive line of research on fixed parameter tractability of integer programming is focused on e...
Sparse input data is data in which most of the data coefficients are zero. Many areas of scientific ...
Motivated by problems in optimization we study the sparsity of the solutions to systems of linear Di...
We continue the investigation of polynomial-time sparsification for NP-complete Boolean Constraint S...
We continue the investigation of polynomial-time sparsification for NP-complete Boolean Constraint S...
We examine how sparse feasible solutions of integer programs are, on average. Average case here mean...
In exact sparse optimization problems on Rd (also known as sparsity constrained problems), one looks...
We introduce a new class of valid inequalities for general integer linear programs, called binary cl...
This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-...
This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-...
We will give new upper bounds for the number of solutions to the inequalities of the shape |F(x, y)|...
The main focus of this paper is a pair of new approximation algorithms for certain integer programs....
An intensive line of research on fixed parameter tractability of integer programming is focused on e...
We present a dual-scaling interior-point algorithm and show how it exploits the structure and sparsi...
We show how to efficiently model binary constraint problems (BCP) as integer programs. After conside...
An intensive line of research on fixed parameter tractability of integer programming is focused on e...
Sparse input data is data in which most of the data coefficients are zero. Many areas of scientific ...
Motivated by problems in optimization we study the sparsity of the solutions to systems of linear Di...
We continue the investigation of polynomial-time sparsification for NP-complete Boolean Constraint S...
We continue the investigation of polynomial-time sparsification for NP-complete Boolean Constraint S...
We examine how sparse feasible solutions of integer programs are, on average. Average case here mean...
In exact sparse optimization problems on Rd (also known as sparsity constrained problems), one looks...
We introduce a new class of valid inequalities for general integer linear programs, called binary cl...
This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-...
This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-...
We will give new upper bounds for the number of solutions to the inequalities of the shape |F(x, y)|...
The main focus of this paper is a pair of new approximation algorithms for certain integer programs....
An intensive line of research on fixed parameter tractability of integer programming is focused on e...
We present a dual-scaling interior-point algorithm and show how it exploits the structure and sparsi...
We show how to efficiently model binary constraint problems (BCP) as integer programs. After conside...
An intensive line of research on fixed parameter tractability of integer programming is focused on e...