M.Sc (CS)

20XC41 OPTIMIZATION TECHNIQUES

3 0 0 3

Prerequisites:   20XC33 LINEAR ALGEBRA

CLASSICAL OPTIMIZATION :Introduction - Classification of optimization problems – Single variable optimization - Multi variable optimization with equality constraints and inequality constraints – solution by the method of Lagrange multipliers - Kuhn –Tucker conditions.              (12)

LINEAR PROGRAMMING: Linear Programming model – Graphical method, Simplex method, Two phase simplex method – Revised Simplex method – Sensitivity Analysis - Dual and Primal problems – Dual Simplex method – Post Optimal Analysis.                                                             (14)

TRANSPORTATION MODEL AND ITS VARIANTS: Transportation problem and its solution – Assignment problem and its solution by Hungarian method                                                               (6)

DYNAMIC PROGRAMMING : Principle of optimality - Forward and Backward Recursion methods – Shortest route problem - Knapsack model – Work force size model                                 (6)

NON LINEAR PROGRAMMING: Direct Search Methods – Univariate method, Hooke and Jeeves method – Indirect search methods – Steepest descent method, Conjugate gradient method.  (7)

Total L:45

TEXT BOOKS:
1. Hamdy A Taha,, “Operations Research :An Introduction”, Pearson Education, 2017.
2. Singiresu S Rao, “Engineering Optimization Theory and Practice”, John Wiley, 2014.

REFERENCES:
1. Hillier F and Lieberman G J, “Introduction to Operations Research”, Tata McGraw Hill, 2014.
2. Wayne Lwinston, “Operations Research: Applications and Algorithms”, Thomson Brooks/Cole, 2004.