In this article, we evaluate the challenges and best practices associated with the Markov
bases approach to sampling from conditional distributions. We provide insights and …

We study the general integer programming problem where the number of variables $ n $ is a
variable part of the input. We consider two natural parameters of the constraint matrix $ A …

Many fundamental NP NP-hard problems can be formulated as integer linear programs
(ILPs). A famous algorithm by Lenstra solves ILPs in time that is exponential only in the …

Integer linear programs of configurations, or configuration IPs, are a classical tool in the
design of algorithms for scheduling and packing problems where a set of items has to be …

We consider integer and linear programming problems for which the linear constraints
exhibit a (recursive) block-structure: The problem decomposes into independent and …

We study an important case of integer linear programs (ILPs) of the form \max{c^Tx\vert\
mathcalAx=b,l≦x≦u,\,x∈Z^nt\} with nt variables and lower and upper bounds …

We consider the standard ILP Feasibility problem: given an integer linear program of the
form {A x= b, x⩾ 0}, where A is an integer matrix with k rows and ℓ columns, x is a vector of ℓ …

The starting point of this paper is the problem of scheduling n jobs with processing times and
due dates on a single machine so as to minimize the total processing time of tardy jobs, ie …

We consider the problem of solving integer programs of the form $\min\{\, c^\intercal
x\\colon\Ax= b, x\geq 0\} $, where $ A $ is a multistage stochastic matrix in the following …

Powerful results from the theory of integer programming have recently led to substantial
advances in parameterized complexity. However, our perception is that, except for Lenstra's …