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Integer Programming: Optimization and Evaluation Are Equivalent

Author(s)
Orlin, James B.; Punnen, Abraham P.; Schulz, Andreas S.
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Abstract
We show that if one can find the optimal value of an integer linear programming problem in polynomial time, then one can find an optimal solution in polynomial time. We also present a proper generalization to (general) integer programs and to local search problems of the well-known result that optimization and augmentation are equivalent for 0/1-integer programs. Among other things, our results imply that PLS-complete problems cannot have “near-exact” neighborhoods, unless PLS = P.
Description
Link to conference publication published by Springer: http://dx.doi.org/10.1007/978-3-642-03367-4
Date issued
2009-01
URI
http://hdl.handle.net/1721.1/68014
Department
Sloan School of Management
Journal
Lecture Notes in Computer Science
Publisher
Springer Science + Business Media B.V.
Citation
Orlin, James B., Abraham P. Punnen, and Andreas S. Schulz. “Integer Programming: Optimization and Evaluation Are Equivalent.” Algorithms and Data Structures. Ed. Frank Dehne et al. Vol. 5664. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. 519-529. (Lecture Notes in Computer Science)
Version: Author's final manuscript
ISSN
0302-9743

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