Optimization

MS&E311

Stanford School of Engineering


Description

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.

Prerequisites

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

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate education section.

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