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

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5233

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DC Field	Value	Language
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	-
Appears in Collections:	MIT Items

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