Column generation (CG) is a well-established method for solving large-scale linear
programs. It involves iteratively optimizing a subproblem containing a subset of columns and …

Column generation is one of the most successful approaches for solving large-scale linear
programming problems. However, degeneracy difficulties and long-tail effects are known to …

The convergence of a column generation algorithm can be improved in practice by using
stabilization techniques. Smoothing and proximal methods based on penalizing the …

We present a new column generation approach based on Machine Learning (ML) for
solving combinatorial optimization problems. The aim of our method is to generate high …

Column generation is a popular method to solve large-scale linear programs with an
exponential number of variables. Several important applications, such as the vehicle routing …

Column generation (CG) is one of the most successful approaches for solving large-scale
linear programming (LP) problems. Given an LP with a prohibitively large number of …

Column Generation (CG) algorithms are instrumental in many areas of applied optimization,
where Linear Programs with an enormous number of columns need to be solved. Although …

Column Generation (CG) is an effective method for solving large-scale optimization
problems. CG starts by solving a subproblem with a subset of columns (ie, variables) and …

Branch-and-price algorithms for the graph coloring problem use an exponentially sized
independent set-based integer programming formulation to produce usually tight lower …

Column Generation (CG) is an iterative algorithm for solving linear programs (LPs) with an
extremely large number of variables (columns). CG is the workhorse for tackling large-scale …