A Computational Analysis of Lower Bounds for Big Bucket Production Planning Problems

Kerem Akartunali (1) , Andrew J. Miller (2, 3)

1 Department of Mathematics and Statistics [Melbourne]
2 IMB - Institut de Mathématiques de Bordeaux
3 Realopt - Reformulations based algorithms for Combinatorial Optimization

In this paper, we analyze a variety of approaches to obtain lower bounds for multilevel production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to our knowledge, have not been presented before. As will be highlighted, understanding the substructures of difficult problems provides valuable insights on why these problems are hard to solve. We conclude with computational results from widely used test sets and discussion of future research.

Domains: Operations Research [math.OC]

Kerem Akartunali, Andrew J. Miller. A Computational Analysis of Lower Bounds for Big Bucket Production Planning Problems. 2009. ⟨hal-00387105⟩