Improving Branch-And-Price Algorithms For Solving One Dimensional Cutting Stock Problem

Branch-and-price is a well established technique for solving large scale integer programming problems. This method combines the standard branch-and-bound framework of solving integer programming problems with Column Generation. In each node of the branch-and-bound tree, the bound is calculated by solving the LP relaxation. The LP relaxation is solved using Column Generation. In this report, we discuss our project on improving the performance of branch-and-price based algorithms for solving the industrial one-dimensional cutting stock problem. In the early part our project, we studied several branch-and-price based algorithms that are available in the literature for solving the cutting stock problem. We write down our findings from the study in this report. In the later part of the project, we worked on a few ideas to improve the performance of the algorithms. We publish the results in the report. We conclude the report by giving some directions for future works.