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Ellipsoidal Mixed-Integer Representability

Alberto Del Pia (delpia***at***wisc.edu)
Jeff Poskin (poskin***at***wisc.edu)

Abstract: Representability results for mixed-integer linear systems play a fundamental role in optimization since they give geometric characterizations of the feasible sets that can be formulated by mixed-integer linear programming. We consider a natural extension of mixed-integer linear systems obtained by adding just one ellipsoidal inequality. The set of points that can be described, possibly using additional variables, by these systems are called ellipsoidal mixed-integer representable. In this work, we give geometric conditions that characterize ellipsoidal mixed-integer representable sets.

Keywords: mixed-integer programming; quadratic programming; representability; ellipsoidal constraints

Category 1: Integer Programming ((Mixed) Integer Nonlinear Programming )

Category 2: Global Optimization (Theory )

Citation: Submitted manuscript

Download: [PDF]

Entry Submitted: 05/30/2016
Entry Accepted: 05/30/2016
Entry Last Modified: 09/15/2017

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