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Local and global lifted cover inequalities for the multidimensional knapsack problem

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>1/04/2008
<mark>Journal</mark>European Journal of Operational Research
Issue number1
Number of pages13
Pages (from-to)91-103
<mark>Original language</mark>English


The 0-1 Multidimensional Knapsack Problem (0-1 MKP) is a well-known (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.