Subject Code: MA7L022	Name: Advanced Techniques in Operations Research	L-T-P: 3-1-0	Credits: 4
Non--Linear Programming Problems: One variable unconstrained optimization, multivariable unconstrained optimisation, Karush-Kuhn-Tucker (KKT) conditions for constrained optimization, quadratic programming, separable programming, convex and non-convex programming, teepest and Quasi-Newton method. Dynamic Programming: Characteristics of dynamic problems, deterministic dynamic programming and probabilistic dynamic programming, Network analysis, Shortest path problems, minimum spanning tree problem, maximum flow problem, minimum cost flow problem, network simplex, interior point methods, stochastic programming, Nonlinear goal programming applications, Geometric Programming. Multi-objective Optimization Problems: Linear and non-linear programming problems, Weighting and Epsilon method, P-norm methods, Gradient Projection Method, STEM method, Convex Optimization. Texts/References Books: S.S. Rao, ‘Engineering Optimization Theory and Practices’, John Wiley and Sons, 2009 M. Ehrgott, ‘Multi-criteria Optimization’, Springer 2006 K.M, Miettien, ‘Non-linear multi-objective optimization’, Kluwers International Series, 2004 K. Deb, ‘Multi-objective evolutionary optimization for product design and manufacturing’, Springer, 2011.