Quantitative Techniques for Decision Making

OBJECTIVE:
• To apply quantitative techniques in modeling and solving business related problems. 

UNIT I INTRODUCTION TO LINEAR PROGRAMMING (LP) 
Relevance of quantitative techniques in management decision making. Linear Programming-formulation, solution by graphical and simplex methods (Primal – Penalty, Two Phase), Special cases. Sensitivity Analysis.

UNIT II LINEAR PROGRAMMING EXTENSIONS
Transportation Models (Minimising and Maximising Problems) – Balanced and unbalanced Problems – Initial Basic feasible solution by N-W Corner Rule, Least cost and Vogel’s approximation methods. Check for optimality. Solution by MODI / Stepping Stone method. Case of Degeneracy. Transhipment Models.

Assignment Models (Minimising and Maximising Problems) – Balanced and Unbalanced Problems. Solution by Hungarian and Branch and Bound Algorithms. Travelling Salesman problem. Crew Assignment Models.

UNIT III DECISION AND GAME THEORIES

Decision making under risk – Decision trees – Decision making under uncertainty.
Game Theory-Two-person Zero sum games-Saddle point, Dominance Rule, Convex Linear Combination (Averages), methods of matrices, graphical and LP solutions.

UNIT IV INVENTORY AND REPLACEMENT MODELS 
Inventory Models – EOQ and EBQ Models (With and without shortages), Quantity Discount Models.
Replacement Models-Individual replacement Models (With and without time value of money) – Group Replacement Models.

UNIT V QUEUING THEORY AND SIMULATION 
Queuing Theory – single and multi-channel models – infinite number of customers and infinite calling source.
Monte Carlo simulation – use of random numbers, application of simulation techniques

OUTCOME:
To understand the applications of
• Linear programming in product mix decisions
• Transportation and assignment in logistics and job allocation scenarios
• Game theory and heuristics of decision making in real time decisions
• Inventory management and replacement models in manufacturing context
• Queuing and simulation in real time scenario optimisation

REFERENCES:

1. N. D Vohra, Quantitative Techniques in Management, Tata Mcgraw Hill, 2010.
2. G. Srinivasan, Operations Research – Principles and Applications, 2nd edition, PHI, 2011.
3. Paneerselvam R., Operations Research, Prentice Hall of India, Fourth Print, 2008.
4. Hamdy A Taha, Introduction to Operations Research, Prentice Hall India, Tenth Edition, Third Indian Reprint 2019.
5. Bernard W.Taylor III, Introduction to Management Science, 9th Edition, Pearson Ed.
6. Frederick & Mark Hillier, Introduction to Management Science – A Modeling and case studies approach with spreadsheets, Tata Mcgraw Hill, 2010.
7. Nagraj B, Barry R and Ralph M. S Jr., Managerial Decision Modelling with Spreadsheets, Second Edition, 2007, Pearson Education.