Exact solution method to solve large scale integer quadratic multidimensional knapsack problems

D. Quadri (), E. Soutif () and P. Tolla ()
Additional contact information
D. Quadri: Université Paris-Dauphine
E. Soutif: Conservatoire des Arts et Métiers
P. Tolla: Université Paris-Dauphine

Journal of Combinatorial Optimization, 2009, vol. 17, issue 2, No 3, 157-167

Abstract: Abstract In this paper we develop a branch-and-bound algorithm for solving a particular integer quadratic multi-knapsack problem. The problem we study is defined as the maximization of a concave separable quadratic objective function over a convex set of linear constraints and bounded integer variables. Our exact solution method is based on the computation of an upper bound and also includes pre-procedure techniques in order to reduce the problem size before starting the branch-and-bound process. We lead a numerical comparison between our method and three other existing algorithms. The approach we propose outperforms other procedures for large-scaled instances (up to 2000 variables and constraints).

Keywords: Integer programming; Separable quadratic function; Linearization; Surrogate relaxation; Branch-and-bound (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10878-007-9105-1

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