- Semester:
III/IV
- Number of credits: 4
Preamble
The elective is useful for both industrial analysis and policy guidance in an organization. It deals with resource allocation, cost minimization, maximization of profits, accomplishing multiple goals and so on. It also helps in measuring the performances of similar units. It identifies the extent of inefficiency, the causes for inefficiency and suggests the extent to which the performance can be improved. This course will provide hands on computer for applications and analysis.
Evaluation Pattern
The evaluation will be done through 40 marks of continuous evaluation and a 60 marks end-semester examination. The 40 marks of evaluation will consist of a mid-term examination of 20 marks (two questions to be attempted over one hour) and a project of 20 marks on Modules 3 and 4. The project topics will be announced by the 4th teaching week of the semester and the projects should be in by the 10th teaching week. All modules will carry equal weight for the three hour end-semester examination.
Module 1: Linear Programming (12 Lectures)
Formulation, the graphical method, the simplex method, duality, degeneracy, sensitivity analysis Special linear programming problems – the assignment problem, transportation problem, linear programming and game theory, linear programming and input output.
Module 2: Extensions in Linear Programming (12 Lectures)
The decomposition method, goal programming- relationships between goal programming and management science /operations research / multiple criteria decision making
Module 3: Concepts of Data Envelopment Analysis (DEA) (12 Lectures)
Basic Concepts: A Decision-Making Unit; Measurement of Efficiency; Frontier Analysis, Mathematical Programming Aspects of DEA: Fractional DEA programme – use of Linear Programming; primal & dual in the format required for DEA; output- maximization and input-minimization DEA models.
Module 4: Applications (12 Lectures)
Economies of Scale: Variable and Constant Returns to Scale and DEA; Technical and scale efficiencies; Computer applications using industry data; Extensions in DEA: Malmquist Productivity Index, Use of Regressions and sensitivity analysis in DEA.
Practical applications using sectoral data
References
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1.
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Dorfman R, Paul Samuelson and Robert Solow (1958): Linear programming and Economic Analysis,
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McGraw- Hill Book company, Inc New York(Module 1,2) |
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2.
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James P Ignizio (1976): Goal Programming and Extensions, Lexington Books, D.C Health and Company,
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Lexington (Module 2) |
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3. |
N.Paul Loomba (1964): Linear Programming: An Introductory Analysis, Tata McGraw –Hill publishing |
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Company Ltd Bombay-New Delhi (Module 1,2) |
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4. |
N.Paul Loomba. Efraim Turban (1974): Applied Programming for Management, Holt, Rinehart & Winston, |
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Inc.New York.( Module 1,2,3) |
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5. |
Ramanathan R (2003) An Introduction to Data Envelopment Analysis A Tool for Performance |
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Measurement, Sage Publications New Delhi (Module 3,4) |
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6. |
Ray Subhash (2004): Data Envelopment Analysis Theory and Techniques for Economics and Operations |
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Research, Cambridge University Press, UK. (Module 3,4) |
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7. |
Tim Coelli - DEAP - Data Envelopment Analysis (Computer) Programme, Centre for Efficiency and |
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Productivity Analysis, Department of Econometrics, University of England, Armidale, Australia. ( Module |
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3,4) |
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M.A. Credit Course 
