SOL PhD Dissertations Stanford University Department of MS&E Systems Optimization Laboratory

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Completed dissertations:

• Kaustuv.
  IPSOL: An Interior Point Solver for Nonconvex Optimization Problems.
  PhD thesis, Stanford University, December 2008. (pdf)

• Hanh Huynh.
  A Large-scale Quadratic Programming Solver Based on Block-LU Updates of the KKT System.
  PhD thesis, Stanford University, September 2008. (pdf)

• Sou-Cheng Choi.
  Iterative Methods for Singular Linear Equations and Least-Squares Problems.
  PhD thesis, Stanford University, December 2006. (pdf)

• Samantha Infeld.
  Optimization of Mission Design for Constrained Libration Point Space Missions.
  PhD thesis, Stanford University, March 2006. (Dec 16, 2005 version: pdf)

• Holly Jin.
  Scalable Sensor Localization Algorithms for Wireless Sensor Networks.
  PhD thesis, University of Toronto (joint research with Stanford University), November 2005.
  Published version:
  M. W. Carter, H. H. Jin, M. A. Saunders, and Y. Ye.
  SpaseLoc: An adaptive subproblem algorithm for scalable wireless sensor network localization,
  SIAM J. on Optimization 17(4), 1102-1128 (2006). (pdf)

• Vinayak (Uday) Shanbhag.
  Decomposition and Sampling Methods for Stochastic Equilibrium Problems.
  PhD thesis, Stanford University, December 2005. (pdf)
  Winner of 2006 A. W. Tucker Prize awarded by the Mathematical Programming Society.

• Che-Lin Su.
  Equilibrium Problems with Equilibrium Constraints: Stationarities, Algorithms, and Applications.
  PhD thesis, Stanford University, September 2005. (pdf)

• Zheng Su.
  Computational Methods for Least Squares Problems and Clinical Trials.
  PhD thesis, Stanford University, June 2005. (pdf)

• Alexis Collomb.
  Dynamic Asset Allocation by Stochastic Programming Methods.
  PhD thesis, Stanford University, December 2004. (pdf)

• Maureen Doyle.
  A Barrier Algorithm for Large Nonlinear Optimization Problems.
  PhD thesis, Stanford University, December 2003. (pdf)

• Carl-Magnus Fransson (Visiting Researcher, 2001-2003).
  Optimization Methods for Robust Control, with Application to Resistive Wall Modes in Tokamaks.
  PhD thesis, Dept of Signals and Systems, Chalmers University of Technology, Goteborg, Sweden, September 2003.

• Byunggyoo Kim.
  Numerical Optimization Methods for Image Restoration.
  PhD thesis, Stanford University, December 2002. (pdf, ps.gz)

• Michael P. Friedlander.
  A Globally Convergent Linearly Constrained Lagrangian Method for Nonlinear Optimization.
  PhD thesis, Stanford University, August 2002. (pdf, ps.gz)

• Kien-Ming Ng.
  A Continuation Approach for Solving Nonlinear Optimization Problems with Discrete Variables.
  PhD thesis, Stanford University, June 2002. (pdf, ps)

• Chih-Hung Lin.
  A Null-Space Primal-Dual Algorithm for Nonlinear Network Optimization.
  PhD thesis, Stanford University, March 2002. (pdf, ps)

• Michael J. O'Sullivan.
  New Methods for Dynamic Programming Over an Infinite Time Horizon.
  PhD thesis, Stanford University, February 2002. (pdf, ps)

• Heiko Pieper.
  Algorithms for Mathematical Programs with Equilibrium Constraints with Applications to Deregulated Electricity Markets.
  PhD thesis, Stanford University, June 2001. (ps)

• Titus F. Dorstenstein.
  Constructive and Exchange Algorithms for the Frequency Assignment Problem.
  PhD thesis, Stanford University, June 2001.

• Angel-Victor de Miguel.
  Two Decomposition Algorithms for Nonconvex Optimization Problems with Global Variables.
  PhD thesis, Stanford University, April 2001. (pdf, ps)

• Marty O'Brien.
  Techniques for Incorporating Expected Value Constraints into Stochastic Programs.
  PhD thesis, Stanford University, June 2000. (pdf)

• Antonino Del Gatto.
  A Subspace Method Based on a Differential Equation Approach to Solve Unconstrained Optimization Problems.
  PhD thesis, Stanford University, June 2000. (pdf, ps)

• Aparna Gupta
  Optimum Asset Allocation with Behavioral Utilities: A Plan for Acquiring and Consuming Retirement Funds.
  PhD thesis, SCCM, Stanford University, May 2000. (pdf)

• Meredith J. Goldsmith.
  Sequential Quadratic Programming Methods Based on Indefinite Hessian Approximations.
  PhD thesis, Stanford University, March 1999. (pdf, ps)

• Erik Boman.
  Infeasibility and Negative Curvature in Optimization.
  PhD thesis, Stanford University, February 1999. (ps.gz)

• William Behrman.
  An Efficient Gradient Flow Method for Unconstrained Optimization.
  PhD thesis, Stanford University, June 1998. (pdf)

Updated: 19 Sep 2002