Integer Programming: Optimization and Evaluation Are Equivalent
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schulz-Punnen 2009.pdf
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https://public.me.com/orlin2
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146.52 KB
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Author(s)
Orlin, James B.
Punnen, Abraham P.
Schulz, Andreas S.
Date Issued
January 2009
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
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
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1007/978-3-642-03367-4_45
