Title page for etd-0022114-091749


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URN etd-0022114-091749
Author Ruei-Chi Lai
Author's Email Address No Public.
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Department Applied Mathematics
Year 2013
Semester 1
Degree Master
Type of Document
Language English
Title A primal-dual infeasible interior point algorithm for linearly
constrained convex programming
Date of Defense 2014-01-21
Page Count 31
Keyword
  • global convergence
  • step length
  • infeasible interior point algorithm
  • linear programming
  • linearly constrained convex programming
  • Abstract Convex minimization has applications in a wide range of disciplines, such as
    automatic control systems, estimation and signal processing, communications and net-
    works, electronic circuit design, data analysis and modeling, statistics (optimal design),
    and nance. With recent improvements in computing and in optimization theory, con-
    vex minimization is nearly as straightforward as linear programming. The theoretical
    part of this thesis follow the work in [1]. This paper rst introduces the primal-dual
    infeasible interior point algorithm for linear programming[1], then uses the model of
    the algorithm in [1] to obtain the primal-dual infeasible interior point algorithm for
    linearly constrained convex programming, and the algorithm has global convergence.
    Advisory Committee
  • Lai-Ji Lin - chair
  • JEN-CHIH YAO - co-chair
  • Ngai-Ching Wong - co-chair
  • Hong-Kun Xu - advisor
  • Files
  • etd-0022114-091749.pdf
  • Indicate in-campus at 99 year and off-campus access at 99 year.
    Date of Submission 2014-01-23

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