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Advanced Management Science Methods

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Course Type Course Code No. Of Credits
Foundation Core SBP2MB834 2

Semester and Year Offered:

Course Coordinator and Team: Anshu Gupta

Email of course coordinator: anshu[at]aud[dot]ac[dot]in

Pre-requisites: Basic course in Operations Research/Management Science and Operations Management at undergraduate or graduate level

Aim: The objective of this course is to develop an understanding of formal quantitative approaches to problem solving using advanced management science methods and their applications.

Course Outcome:

After completing this course, student will be able to

  1. Define management problems and formulate mathematical models with respect to these problems.
  2. Use advance management science methods for mathematical problem solving.
  3. Analyze problems using management science methods and use software tools for problem solving.
  4. Draw meaningful interpretations and recommendations for decision making based on the solutions obtained from mathematical models.

Brief description of modules/ Main modules:

Unit 1: Classical Optimization Methods and Non-Linear Programming

Unconstrained optimization of single and multi-variable functions; Constrained single and multivariable optimization; Select non-linear programming formulations and solution methods

Unit 2: Dynamic Programming

Bellman’s principle of optimality; Developing optimal decision rule; Applications of dynamic programming under certainty

Unit 3: Simulation Modelling

Introduction to types of simulation; Monte Carlo simulation; Simulations of inventory, queuing, investment and PERT problems

Unit 4: Sequencing Problems

Algorithms and applications of open shop, job shop and flow shop problems

Unit 5: Analytical Hierarchical Process

Introduction to multi-criteria decision making using AHP, Saaty scale, AHP algorithm and applications

Unit 6: Further discussions on fundamental decision science methods

Advanced waiting line and inventory management models, PERT cost estimation, Goal programming, Time minimization transportation models

Assessment Details with weights:

  • Case Analysis 15% (throughout semester)
  • Research paper review 15% (throughout semester)
  • Project 10% (throughout semester)
  • Quiz 20% (5th Week)
  • End semester 40% (9th Week)

Reading List

  • Anderson, D.R., Sweeney, D.J., and Williams, T.A. (2012). An Introduction to Management Science: Quantitative Approaches to Decision Making, 13th edition, Cengage Learning
  • Hillier, F. and Lieberman, G. (2012). Introduction to Operations Research: Concepts and Cases, 9th Edition, Tata McGraw Hill Education Private Limited
  • Hillier, F. and Lieberman, G. (2015). Introduction to Management Science: A Modelling and Case Studies Approach with Spreadsheets, 4th Edition, Tata McGraw Hill Education Private Limited
  • Powell, S.G., and Barker, K.R. (2014).Management Science: The Art Of Modelling With Spreadsheets, 4th Edition, John Wiley and Sons
  • Sharma, J.K. (2009). Operations Research: Theory and Applications, 4th Edition, Macmillan India Limited
  • Winston, W.L. and Albright, S.C. (2014). Practical Management Science, 5th Edition, Cengage Learning.

Additional Reference

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