Quadratically Convergent Adaptive Self-Regular Predictor-Corrector Interior Point Algorithms

Event Details
  • Date/Time:
    • Thursday October 23, 2003
      2:00 pm - 12:00 am
  • Location: ISyE 303 - Groseclose
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Contact
Barbara Christopher
Industrial and Systems Engineering
Contact Barbara Christopher
404.385.3102
Summaries

Summary Sentence: Quadratically Convergent Adaptive Self-Regular Predictor-Corrector Interior Point Algorithms

Full Summary: Quadratically Convergent Adaptive Self-Regular Predictor-Corrector Interior Point Algorithms

First we review the basic concepts of self-regular proximity based Interior Point Method that allowed a complexity improvement of large-update, large-scale interior point methods. Some intriguing properties of a specific self-regular proximity function are discussed and we will show that the neighborhood used in our predictor-corrector algorithm contains the infinity norm neighborhood that is used in all practical implementations of IPMs.

Then a new adaptive self-regular predictor-corrector algorithm is presented where the corrector step is defined by our self-regular proximity and the predictor step is either a self-regular or an affine-scaling step. Polynomial worst case complexity [O(sqrt(n) log(n) L) in the best case] and asymptotic quadratic convergence rate is established.

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 8, 2010 - 7:42am
  • Last Updated: Oct 7, 2016 - 9:52pm