On Warm Starts for Interior Methods

  • A. Forsgren
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 199)

Abstract

An appealing feature of interior methods for linear programming is that the number of iterations required to solve a problem tends to be relatively insensitive to the choice of initial point. This feature has the drawback that it is difficult to design interior methods that efficiently utilize information from an optimal solution to a “nearby” problem. We discuss this feature in the context of general nonlinear programming and specialize to linear programming. We demonstrate that warm start for a particular nonlinear programming problem, given a near-optimal solution for a “nearby” problem, is closely related to an SQP method applied to an equality-constrained problem. These results are further refined for the case of linear programming.

keywords

nonlinear programming linear programming interior method warm start 

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Copyright information

© International Federation for Information Processing 2006

Authors and Affiliations

  • A. Forsgren
    • 1
  1. 1.Optimization and Systems Theory, Department of MathematicsRoyal Institute of TechnologyStockholmSweden

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