Stanford School of Engineering


Understanding applications, theories and algorithms for finite-dimensional linear and nonlinear optimization problems with continuous variables can lead to high performing design and execution. This course explores algorithms for unconstrained optimization, and linearly and nonlinearly constrained problems, used in communication, game theory, auction and economics.


MATH113, MATH115 or equivalent.

  • 1 year of college level calculus (through calculus of several variables, such as CME100 and MATH 51)
  • Background in statistics, experience with spreadsheets recommended.
  • An undergraduate degree with a GPA of 3.0 or equivalent

Topics include

  • Convex analysis
  • Duality
  • First- and second-order optimality conditions
  • Sensitivity

Course Availability

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