In this paper we present a generalization and a computational improvement of the Bound Improvement Sequence Algorithm. The main computational burden of this algorithm consists in determining whether there exists a feasible point on the objective hyperplane, when the algorithm encounters a fixed point. By generalizing the algorithm, such that the objective function and constraints are treated alike, the number of fixed points that are required can be reduced. The computational results that we report allow us to conclude that the number of fixed points can generally be reduced for loosely constrained problems. For this class of problems the new algorithm appears to be more efficient than a standard MIP code such as FMPS.
- Integer programming
- Lagrange multipliers