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About Lagrangian Methods in Integer Optimization

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  • Antonio Frangioni

Abstract

It is well-known that the Lagrangian dual of an Integer Linear Program (ILP) provides the same bound as a continuous relaxation involving the convex hull of all the optimal solutions of the Lagrangian relaxation. It is less often realized that this equivalence is effective, in that basically all known algorithms for solving the Lagrangian dual either naturally compute an (approximate) optimal solution of the “convexified relaxation”, or can be modified to do so. After recalling these results we elaborate on the importance of the availability of primal information produced by the Lagrangian dual within both exact and approximate approaches to the original (ILP), using three optimization problems with different structure to illustrate some of the main points. Copyright Springer Science + Business Media, Inc. 2005

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  • Antonio Frangioni, 2005. "About Lagrangian Methods in Integer Optimization," Annals of Operations Research, Springer, vol. 139(1), pages 163-193, October.
    • Handle: RePEc:spr:annopr:v:139:y:2005:i:1:p:163-193:10.1007/s10479-005-3447-9
    DOI: 10.1007/s10479-005-3447-9
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    Lagrangian dual; integer linear programs;

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