Optimization I | Department of Mathematics

Optimization I

A Major Elective for B.Sc. (Research) Mathematics.

Credits (Lec:Tut:Lab): 3:1:0 (3 lectures and 1 tutorial weekly)

Prerequisites: MAT 160 (Linear Algebra) or MAT 104 (Mathematical Methods II)

Overview: Optimization deals with the problem of establishing the best & worst cases for a given situation. This course deals mostly with the special case of linear programming, which is commonly applied to problems of business and economics as well as industrial problems in transportation, energy and telecommunication.

Detailed Syllabus:

  1. Mathematical modeling and optimization problem formulation
  2. Application of optimization (linear case)
  3. Geometry of linear optimization
  4. Simplex method
  5. Duality theory
  6. Sensitivity analysis
  7. Robust optimization
  8. Graphs and Network flow problems
  9. Discrete optimization or Integer programming formulations
  10. Non-linear optimization – introduction and applications


Main References:

  1. Linear Programming by G. Hadley, Narosa, 2000
  2. Understanding and Using Linear Programming by J. Matousek and B. Gärtner, Springer, 2006
  3. Introduction to Linear Optimization by D. Bertsimas and J. Tsitsiklis, Athena Scientific, 1997
  4. Theory of Linear and Integer Programming by A. Schrijver, Wiley, 1998
  5. Operations Research: An Introduction by H. Taha, Pearson, 2012

Past Instructors: Samit Bhattacharyya


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