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CourseOutline
Course Name: Quantitative Methods for Business ‐ II Instructor(s): Prof. Amit Sachan and Prof. Sasadhar Bera E‐mail: [email protected], [email protected] Objective: The objective of this course is to learn how to apply a particular quantitative technique in a business decision making. This introductory course covers optimization techniques like linear programming, integer programing, transportation problems, multi‐objective decision (goal programming), multi criteria decision making (AHP), Forecasting, and Simulation. These techniques are used in a wide variety of realistic applications including manufacturing operation, Service operations, finance and marketing application areas. Most of the course is focused on in modeling, understanding the implications and limitations of the model with examples. The optional project provides an opportunity for students to develop their skills in identifying and structuring problems. Skills developed include identification of the proper modeling tool for the business problem, conducting proper analysis using the tool and developing recommendations for the original business problem. Textbook:
1) An introduction to management science: Quantitative approaches to decision making –
Anderson, Sweeney, Williams, and Martin
2) Introduction to management science with spreadsheets. ‐ William J. Stevenson and Ceyhun Ozgur.
3) Quantitative analysis for management ‐ Barry Render, Ralph M Stair, Michael E Hanna, T. N. Badri, Pearson India Pvt. Ltd.
4) Operations research: An Introduction ‐ H. A. Taha
Homework Assignments Homework problems will be assigned regularly (electronic or hard‐copy). The solved assignments should be legible, clearly documented and prepared according to instructions.
Grading The overall grade will be computed as follows:
Sr. No. Component Weightage (%)
Open Book /Closed
Instructor
a) Quiz 15 Prof. Amit Sachan
b) Take home Assignments 10
c) Class Participation 5
d) Mid Term Examination 20 Open
e) Quiz 8 Prof. Sasadhar Bera
f) Take home Assignments/Case Presentation
15
g) Class Participation 7
h) End Term Examination 20 Open
Course Outline
Sessions Topic Instructor
1 Introduction to MS Prof. Amit Sachan
2 LP Formulation
3‐4 Graphical solution and Spread Sheet Solution
5‐6 Sensitivity and Duality
7‐8 Transportation, Transshipment and Assignment problem
9‐10 Integer Programming
11‐12 Goal Programming Prof. Sasadhar Bera
13‐14 Analytical Hierarchy Process
15 Markov Analysis
16‐18 Forecasting
19‐20 Simulation