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  • 6:21 PM, Monday, 18 Oct 2021

Course Postgraduate
Semester Electives
Subject Code AVC867
Subject Title Optimization


Motivation, mathematical review , matrix factorizations, sets and sequences, convex sets and functions, linear programming and simplex method, Weierstrass' theorem, Karush Kuhn Tucker optimality conditions, algorithms, convergence, unconstrained optimization, Line search methods, method of multidimensional search, steepest descent methods, Newton's method, modifications to Newton's method, trust region methods, conjugate gradient methods, quasi‐Newton's methods. Constrained optimization, penalty and barrier function methods, augmented Lagrangian methods, polynomial time algorithm for linear programming, successive linear programming, successive quadratic programming.

Heuristic methods, evolutionary computing, genetic, bee, and ant algorithms

Text Books

Same as Reference

  1. R. Fletcher Practical Optimization (2nd Edition) John Wiley & Sons, New York, 1987.
  2. M.S.Bazaraa , H.D.Sherali and C.Shetty , Nonlinear Programming, Theory and Algorithms, JohnWiley and Sons, New York, 1993.
  3. David G. Luenberger, Optimization by Vector Space Methods, John Wiley and Sons, 1969.
  4. David G. Luenberger, Linear and Nonlinear Programming, Springer 2008.
  5. Stephen P. Boyd, Lieven Vandenberghe, Convex Optimization, Cambridge University Press, 2004.