STANFORD UNIVERSITY

MS&E 315 Numerical Optimization

Course Information

Comprehensive notes will be provided. There is no exam. A grade will be assessed on about eight homework sets and a MATLAB project.

Homework Policies

  • Each homework is due in class at 11:00am, usually one week after being assigned.
  • One late homework is allowed without explanation. The late homework is due in class at 11:00am on Wednesday of the following week.
  • Anyone wishing to be excused submitting additional homework on time must make a request at least one day prior to its due date.
  • The Stanford Honor Code applies to each assignment, both in and out of class. Copying homework from another student, past or present, is forbidden. However, collaboration is acceptable to a degree. Each student must record on the homework with whom and on what problems the students collaborated.
  • Please cite the references you use.

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Final Project

  • The purpose of the project is to gain some experience in the difficulties of defining a problem, implementing an algorithm, and interpreting output; as well as to gain some appreciation for good optimization algorithms.
  • We shall assign the class a project topic. Students who wish to do something different than the assigned project must submit a proposal for approval.
  • Projects are due at the end of the quarter.

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Textbooks

  • P. E. Gill, W. Murray, and M. H. Wright, Practical Optimization, Academic Press.
  • J. Nocedal, S. J. Wright, Numerical Optimization, Springer Verlag.
  • D.Bertsekas, Nonlinear Programming, Athena Scientific.

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Supplementary Texts

  • P. E. Gill, W. Murray and M. H. Wright, Numerical Methods for Linear Algebra and Optimization: Volume 1, Addison-Wesley.
  • P. E. Gill and W. Murray, Numerical Methods for Constrained Optimization, Academic Press.
  • R. Fletcher, Practical Methods for Optimization, Wiley.

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Lovely Classics

  • A. V. Fiacco and G. P. McCormick, Nonlinear Programming: Sequential Unconstrained Minimation Techniques, SIAM.
  • O. L. Mangasarian, Nonlinear Programming , SIAM

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Optimization

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Linear Algebra

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