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An exact primal–dual penalty method approach to warmstarting interior-point methods for linear programming
Journal article   Peer reviewed

An exact primal–dual penalty method approach to warmstarting interior-point methods for linear programming

Hande Benson and David Shanno
Computational optimization and applications, v 38(3), pp 371-399
Dec 2007

Abstract

Convex and Discrete Geometry Operations Research/Decision Theory Penalty methods Linear programming Mathematics Statistics, general Operations Research, Mathematical Programming Interior-point methods Optimization Warmstarting
One perceived deficiency of interior-point methods in comparison to active set methods is their inability to efficiently re-optimize by solving closely related problems after a warmstart. In this paper, we investigate the use of a primal–dual penalty approach to overcome this problem. We prove exactness and convergence and show encouraging numerical results on a set of linear and mixed integer programming problems.

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Collaboration types
Domestic collaboration
Web of Science research areas
Mathematics, Applied
Operations Research & Management Science
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