Osmania University - M.Sc.Stastitics - 4 - Elective : Advanced Operations Research

Elective : Advanced Operations Research

Unit–I
Non linear Programming Problem: Formulation Generalized Lagrange multiplier technique. Kuhn – Tucker necessary and sufficient conditions for optimality of an NLPP, Walfes and Beales Algorithms for solving QPP.

Unit–II
Dynamic Programming: Principle of optimality, solution of LPP by dynamic programming technique, Knapsack problem by Dynamic Programming Technique.
General goal programming model and formulation of its objective function. Solutions to linear programming and linear integer goal programming.

Unit–III
S-S policy for inventory and its derivation in the case of exponential demand; Models with variable supply and models for perishable items. Sequencing and scheduling problems: 2 machine n job and 3 machine n-job problems with identical machine sequence for all jobs; 2–job n-machine problem. Branch and Bound method for solving Travelling Salesman Problem.

Unit–IV
Stochastic Programming Problem; analysis of chance constrained linear programming under zero order, non randomised decision rule, deterministic equivalent of chance constraints with reference to Normal and Cauchy distributions. Linear Fractional Programming Problem and its application and use. Separable Programming Problem: Piecewise linearisation method.

REFERENCES:

1. Taha, H.A.(1982): Operations Research : An Introduction; MacMillan
2. Hillier F.S. and Leiberman,G.J.(1962) : Introduction to Operations Research; Holdon Day
3. Kantiswarup;Gupta P.K. and Singh,M.N.(1985) : Operations Research; Sultan Chand
4. Philips, D.T.,Ravindran,A. and Solbeg,J.(2000) : Operations Research principles and practice.
5. Sharma,S.D.: Operations Research

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