The splitting of variables and constraints in the formulation of integer programming models
The splitting of variables and constraints in the formulation of integer programming models
The splitting of variables in an integer programming model into the sum of other variables can allow the constraints to be disaggregated, leading to a more constrained (tighter) linear programming relaxation. Well known examples of such reformulations are quoted from the literature. They can be viewed as instances of some general methods of performing such reformulations, namely disjunctive formulations, partial network reformulations and a method based on the introduction of auxiliary variables.
623-628
Williams, H.P.
4f620625-0c8e-463a-85c0-703b05c83d27
Brailsford, S.C.
634585ff-c828-46ca-b33d-7ac017dda04f
August 1997
Williams, H.P.
4f620625-0c8e-463a-85c0-703b05c83d27
Brailsford, S.C.
634585ff-c828-46ca-b33d-7ac017dda04f
Williams, H.P. and Brailsford, S.C.
(1997)
The splitting of variables and constraints in the formulation of integer programming models.
European Journal of Operational Research, 100 (3), .
(doi:10.1016/S0377-2217(96)00236-6).
Abstract
The splitting of variables in an integer programming model into the sum of other variables can allow the constraints to be disaggregated, leading to a more constrained (tighter) linear programming relaxation. Well known examples of such reformulations are quoted from the literature. They can be viewed as instances of some general methods of performing such reformulations, namely disjunctive formulations, partial network reformulations and a method based on the introduction of auxiliary variables.
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Published date: August 1997
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Local EPrints ID: 36255
URI: http://eprints.soton.ac.uk/id/eprint/36255
ISSN: 0377-2217
PURE UUID: ea991830-4d76-4ef2-8ee3-2bb71d1fc7a0
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Date deposited: 12 Feb 2007
Last modified: 16 Mar 2024 02:41
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H.P. Williams
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