Computational advances in solving Mixed Integer Linear Programming problems To Professor Sauro Pierucci for leadership in Process Systems Engineering

In this paper, we identify some of the computational advances that have been contributing to the efficient solution of mixed-integer linear programming (MILP) problems. Recent features added to MILP solvers at the algorithmic level and at the hardware level have been contributing to the increasingly efficient solution of more difficult and larger problems. Therefore, we will focus on the main advances in terms of hardware, and algorithms in one commercial solver to demonstrate the advantages and disadvantages of the recent features. Special attention is given to the utilization of multiple threads, parallelization modes, and the integration of heuristics with the branch and cut algorithm. Two problems are used to show the advantages of some of the new options. The results show that while some of the new features may help on the solution of difficult problems, they can also reduce the performance on relatively easy problems.