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Course Info

  • Course Number / Code:
  • 6.252J (Spring 2003) 
  • Course Title:
  • Nonlinear Programming 
  • Course Level:
  • Graduate 
  • Offered by :
  • Massachusetts Institute of Technology (MIT)
    Massachusetts, United States  
  • Department:
  • Electrical Engineering and Computer Science 
  • Course Instructor(s):
  • Prof. Dimitri Bertsekas

  • Course Introduction:

  • 6.252J / 15.084J Nonlinear Programming

    Spring 2003

    Course Highlights

    This course features a full set of lecture notes, in addition to other materials used by students in the course. The materials are largely based on the textbook, Nonlinear Programming: 2nd Edition, written by Professor Dimitri Bertsekas (see the publisher's site for more information).

    Course Description

    6.252J is a course in the department's "Communication, Control, and Signal Processing" concentration. This course provides a unified analytical and computational approach to nonlinear optimization problems. The topics covered in this course include: unconstrained optimization methods, constrained optimization methods, convex analysis, Lagrangian relaxation, nondifferentiable optimization, and applications in integer programming. There is also a comprehensive treatment of optimality conditions, Lagrange multiplier theory, and duality theory. Throughout the course, applications are drawn from control, communications, power systems, and resource allocation problems.

    Technical Requirements

    Any number of development tools can be used to compile and run the .fortran files found on this course site. Please refer to the course materials for any specific instructions or recommendations.


This course content is a redistribution of MIT Open Courses. Access to the course materials is free to all users.

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