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A Comparison of Mixed-Integer Programming Models for Non-Convex Piecewise Linear Cost Minimization Problems

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dc.creator Croxton, Keely L.
dc.creator Gendon, Bernard
dc.creator Magnanti, Thomas L.
dc.date 2004-05-28T19:29:19Z
dc.date 2004-05-28T19:29:19Z
dc.date 2002-07
dc.date.accessioned 2013-10-09T02:38:31Z
dc.date.available 2013-10-09T02:38:31Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/5233
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description We study a generic minimization problem with separable non-convex piecewise linear costs, showing that the linear programming (LP) relaxation of three textbook mixed integer programming formulations each approximates the cost function by its lower convex envelope. We also show a relationship between this result and classical Lagrangian duality theory.
dc.format 1744 bytes
dc.format 729124 bytes
dc.format application/pdf
dc.language en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center
dc.relation Operations Research Center Working Paper;OR 363-02
dc.subject piecewise-linear, integer programming, linear relaxation, Lagrangian relaxation.
dc.title A Comparison of Mixed-Integer Programming Models for Non-Convex Piecewise Linear Cost Minimization Problems
dc.type Working Paper


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