Core Courses

  • STOR 415: Introduction to Optimization
    • Level: An undergraduate course in Optimization
    • Credits: 3
    • Topics:  Mathematical optimization models, terminologies and concepts in optimization, linear and nonlinear programming, geometry of linear programming, simplex methods, duality theory in linear programming, sensitivity analysis,  convex quadratic programming, introduction of convex programming.
    • Software tools: Excel, GAMS, Matlab, and CVX
    • Prerequisite: MATH 547.
    • Time: Every fall and spring semester.
    • Instructors: Shu Lu, Gabor Pataki, and Quoc Tran-Dinh.
  • STOR 612: Foundations of Optimization
    • Level: A first-year graduate course
    • Credits: 3
    • Content:  STOR 612 consists of three major parts: linear programming, quadratic programming, and unconstrained optimization.
      • Topics: Modeling, theory and algorithms for linear programming; modeling, theory and algorithms for quadratic programming; convex sets and functions; first-order and second-order methods such as stochastic gradient methods, accelerated gradient methods and quasi-Newton methods for unconstrained optimization.
    • Prerequisite: Multivariable calculus and linear algebra.
    • Time: Every fall semester.
    • Instructor: Shu Lu, Gabor Pataki, and Quoc Tran-Dinh
  • STOR 614: Advanced Optimization
    • Level: A graduate course in Optimization with an emphasis on foundation theory and solution methods.
    • Credits: 3
    • Topics: STOR 614 consists of three major parts: Integer programming, conic programming, and nonlinear optimization. Topics: modeling, theory and algorithms for integer programming; second-order cone and semidefinite programming; theory and algorithms for constrained optimization; dynamic programming; networks.
    • Prerequisites: Multivariable calculus and linear algebra.
    • Time: Every spring semester.
    • Instructors: Shu Lu, Gabor Pataki, and Quoc Tran-Dinh

Special Topics Courses

  • STOR 893: Optimization for Machine Learning and Data Analysis (Q. Tran-Dinh, Fall 2020).
  • STOR 892: Selected Topics on Numerical Methods for Modern Optimization in Data Analysis (Q. Tran-Dinh, Fall 2018)
  • STOR 892: Advanced Topics in Optimization, Integer Programming and Semidefinite Programming (G. Pataki, Spring 2018)
  • STOR 892: Selected Topics in Modern Convex Optimization (Q. Tran-Dinh, Spring 2017)
  • STOR 891: Convex Analysis and Nonlinear Optimization (S. Lu, Fall 2015)
  • STOR 890: Nonlinear programming (S. Lu, Spring 2013, Spring 2010)
  • SAMSI: Numerical Optimization and Applications (SAMSI)