Integer (linear) programs are a standard way of formalizing a vast array of optimization problems in industry, services, management, science, and technology....

This paper addresses the solution of the capacitated minimum cost flow problem on a network containing \(n\) nodes and \(m\) arcs. Satisfying necessary ...

This paper describes a vector space decomposition algorithmic framework for linear programming guided by dual feasibility considerations. The resolution pro...

This paper describes three recent tools for dealing with primal degeneracy in linear programming. The first one is the Improved Primal Simplex (IPS) algor...

Given a linear program (LP ) with m constraints and n lower and upper bounded variables, any solution \(x^0\) to LP can be represented as a nonne...

This paper focuses on the resolution of the capacitated minimum cost flow problem on a network comprising <i>n</i> nodes and <i>m</i> arcs. We present a met...

Column generation for solving linear programs with a huge number of variables alternates between solving a master problem and a pricing subproblem to add var...

Column generation for solving linear programs with a huge number of variables alternately solves a (restricted) master problem and a pricing subproblem to ad...

Column generation has become a powerful tool in solving large scale integer programs. It is well known that most of the often reported compatibility issues ...

We give a didactic introduction to the use of the column generation technique in linear and in particular in integer programming. We touch on both, the relev...

Dantzig-Wolfe decomposition and column generation, devised for linear programs, is a success story in large scale integer programming. We outline and relate ...