The 0-1 Multidimensional Knapsack Problem (0-1 MKP) is a wellknown (and strongly NP-hard) combinatorial optimization problem with many applications. Up to now, the majority of upper bounding techniques for the 0-1 MKP have been based on Lagrangian or surrogate relaxation. We show that good upper bounds can be obtained by a cutting plane method based on lifted cover inequalities (LCIs). As well as using traditional LCIs, we use some new `global' LCIs, which take the whole constraint matrix into account.
Konstantinos Kaparis, Adam N. Letchford