DA 223-O Operations Research 3:1 (Jan 2022)

Course Instructor: M. Mathirajan, MGMT

Course description: : Elective for M.Tech. (Online) DSBA. This course is aimed to be an introductory graduate-level (200-series) course.

Syllabus

Introduction to Operations Research (OR) / Prescriptive Analytics Applications; General Framework of Mathematical Programming; Linear Programming (LP) - Formulation of BIG (Business, Industry and Government) Problems as LP Model, Solving LP Models using Graphical Approach and Optimization Package(s) : LINDO and LINGO, Sensitivity Analysis, Duality, and Case Studies; Transportation and Assignment Models and its applications with sensitivity analysis; Integer Programming (IP) - Formulation of BIG Problems as IP Model, Solving IP Models using Optimization Package(s), and Case Studies; Heuristic Programming (HP) - Concept of Heuristic, Applications of Simple and Meta Heuristic, and Case Studies; Dynamic Programming (DP) - Formulation of BIG Problems as DP Model, and Case Studies; Goal Programming (GP) - Formulation of BIG Problems as GP Model, Solving GP Models using Optimization Package(s), and Case Studies; Multi-Attribute Decision Making Methods - Introduction Data Envelopment Analysis (DEA) and Analytical Hierarchy Process (AHP) with examples; and Introduction to Monte Carlo Simulation with Examples.

Textbooks / References

  1. Wayne L Winston. Operations Research: Applications and Algorithms (4th Edition). Duxbury Press. An Imprint of Wadsworth Publishing Company, Belmont, California, USA.
  2. Wayne L Winston and S. Christian Albright. Practical Management Science (4th Edition). South-Western College Publishing. South-Western Cengage Learning
  3. Anderson, Sweeney and Williams. An Introduction to Management Science: Quantitative Approaches to Decision Making (14th Edition). South-Western College Publishing.
  4. A. Ravindran, Don T. Phillips and James J. Solberg. Operations Research: Principles and Practice (2nd Edition). Wiley.
  5. (Reference) U Dinesh Kumar, Business Analytics: The Science of Data-Driven Decision Making, Wiley India, 2017.
  6. (Reference) William P Fox, Mathematical Modeling for Business Analytics, CRC Press. Taylor & Francis Group, LLC. 2018.
  7. (Reference) Abben Asllani, Business Analytics with Management Science Models and Methods. Person Education 2015.
  8. (Reference) Stephen G Powell and Kenneth R Baker, Business Analytics: The Art of Modelling with Spreadsheets. John Wiley & Sons. 2017.

Prerequisites: None

Grading:

  • Homeworks 20%
  • Midterm 30%
  • Term Paper 20%
  • Final exam 30%.