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Programme PGP Term IV Academic Year 2021-22

Course title Advanced Mathematical Modeling for Managerial Decisions Area Production & Quantitative Methods Credits 1.25

Instructor(s)
Prof. Sachin Jayaswal

Course Description & Objectives
Introduction: 
Course content: Though there are many useful underlying theories in Operations Research (OR)/Management Science (MS), which are important to know, the main strength of the subject lies in its ability to solve real-world practical problems. Journals in Operations Research/Management Science (OR/MS), especially Interfaces, document success stories of mathematical programming models and OR/MS techniques in solving real world complex decision problems. One estimate puts the amount of savings every OR/MS project achieves at either 40 million dollars, or 30 percent of the total project cost, whichever is greater. It is clear, even though the savings reported are often exaggerated, that there are tremendous savings possible in many areas by adopting a formal, mathematical, decision making process for managerial decisions. However, mathematically modeling a problem is as much an art as it is a science, and the best way to master it, like any other art, is through practice. However, more often than not, there is no unique way to model a given problem, and science comes into play in telling a more efficient formulation from a less efficient one.

Objectives: 
The course aims to achieve the following objectives:
1. Train participants to develop mathematical models to model real-world managerial problems, and to use OR/MS tools to solve them. This will be done through modeling real-world problems, drawn from diverse areas of management: Product Line Design from Marketing; Paper Recycling from Environment; Combinatorial Auctions, Investments for Electricity Generation from Finance; Supply chain network design, Supplier selection, Assembly line balancing, Job Scheduling, Freight Allocation with Lane Cost Balancing problem, Milk Collection problem from Operations/Logistics & Supply Chain; Bandwidth Packing, Selecting Telecommunication Carriers from Telecommunications.
2.To train participants understand the differences between alternate model choices, and identify one that is computationally more efficient. 
3. To train participants in the use of a AMPL (A Mathematical Modeling Language) for modeling and solving large problems arising in real world.

Pedagogy
To achieve the above stated objectives, each session will typically begin with a discussion of a complex real-world business/management problem, as reported in journals like Interfaces, European Journal of Operational Research, Management Science, Operations Research, Marketing Science, and will close with a mathematical model and the optimal solution for the problem discussed. Participants will be encouraged to display their own creativity in arriving at their models in class with the help/hints from the instructor. Wherever possible, emphasis will be on arriving at alternate mathematical models for the same problem, and to show how/why one is computationally better than others. An important component of the course is group assignments/project in which participants will have the opportunity to apply their learnings from the course.