Optimization for Decision Making

Optimization for Decision Making

This course is part of Analytics for Decision Making Specialization

Instructor: Soumya Sen

Access provided by Zain Group

8,890 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

90 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

90 reviews

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Microsoft Excel

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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This course is part of the Analytics for Decision Making Specialization

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There are 4 modules in this course

In this data-driven world, companies are often interested in knowing what is the "best" course of action, given the data. For example, manufacturers need to decide how many units of a product to produce given the estimated demand and raw material availability? Should they make all the products in-house or buy some from a third-party to meet the demand? Prescriptive Analytics is the branch of analytics that can provide answers to these questions. It is used for prescribing data-based decisions. The most important method in the prescriptive analytics toolbox is optimization. This course will introduce students to the basic principles of linear optimization for decision-making. Using practical examples, this course teaches how to convert a problem scenario into a mathematical model that can be solved to get the best business outcome. We will learn to identify decision variables, objective function, and constraints of a problem, and use them to formulate and solve an optimization problem using Excel solver and spreadsheet.

Prescriptive analytics is a part of business analytics that is aimed at prescribing solutions to decision problems. The most important modeling technique within prescriptive analytics is optimization. In this module, we will learn how to recognize contexts where it can be applied and get introduced to the basics of linear optimization.

What's included

11 videos1 reading2 assignments1 discussion prompt

11 videos Total 91 minutes

"Analytics for Decision Making" Specialization Overview 8 minutes
"Optimization for Decision Making" Course Overview 11 minutes
Meet Your Instructor: Soumya Sen 9 minutes
Module 1 Overview: An Introduction to Linear Programming 1 minute
Modeling Approaches to Decision Making 10 minutes
Applications of Optimization – Part 1 10 minutes
Applications of Optimization – Part 2 8 minutes
How to Setup a Linear Optimization Problem 12 minutes
Oak Barrel Brewery: An Example Linear Program Problem 10 minutes
Luxury Sofas Problem: A Practice Exercise 4 minutes
Solution to the Luxury Sofas Practice Problem 7 minutes

1 reading Total 10 minutes

Read this article on Optimization in Prescriptive Analytics 10 minutes

2 assignments Total 120 minutes

Module 1 Graded Exercise 60 minutes
Module 1 Practice Exercise 60 minutes

1 discussion prompt Total 30 minutes

What are some problems you could reformulate into optimization problems? 30 minutes

In order to solve linear optimization problems (i.e., linear programs), we can use graphical methods for basic example problems. For higher dimensional problems, we will use tools like Excel Solver later in the course. The benefit of using graphical methods is that it gives us an intuition into how these problems can be solved.

What's included

8 videos2 assignments

8 videos Total 61 minutes

Module 2 Overview 2 minutes
Solving Linear Optimization Problems - Part 1a 10 minutes
Solving Linear Optimization Problems - Part 1b 8 minutes
Solving Linear Optimization Problems - Part 2 10 minutes
Solving Linear Optimization Problems - Part 3 5 minutes
Example Problem: How Many Items of Two Products Should a Manufacturer Produce? (Part 1) 7 minutes
Example Problem: How to Plot the Feasible Region of the Problem (Part 2) 8 minutes
Example Problem: Finding the Optimal Solution for the Problem (Part 3) 11 minutes

2 assignments Total 120 minutes

Module 2 Graded Exercise: Giapetto's Woodcarving Company 60 minutes
Module 2 Practice Exercise: A Retail Butcher Shop 60 minutes

In this module we will explore what happens when the model parameters are changed. We will also look at special cases of linear optimization problems.

What's included

7 videos2 assignments

7 videos Total 49 minutes

Module 3 Overview: Alternative Specifications and Shadow Prices 1 minute
Impact of Changes to Model Parameters - Part 1 11 minutes
Impact of Changes to Model Parameters - Part 2 10 minutes
What to Do When There are Multiple Optimal Solutions 9 minutes
Redundant Constraints 6 minutes
Unbounded Solutions 8 minutes
Infeasible Solution 4 minutes

2 assignments Total 120 minutes

Module 3 Graded Exercise: Dorian Auto Manufacturer 60 minutes
Module 3 Practice Exercise: An Automobile Manufacturer 60 minutes

Having learned how to formulate linear optimization problem and the graphical methods for solving them, we are now going to start solving larger problems using Excel Solver. This module provides an overview of how to set up and solve these decision problems using Excel.

What's included

13 videos2 readings2 assignments

13 videos Total 75 minutes

Module 4 Overview: Modeling & Solving Linear Problems in Excel 1 minute
Introduction to Spreadsheet Solvers 4 minutes
Steps in Implementing an LP Model in Excel 6 minutes
Organizing LP model data in Excel 9 minutes
Optimal Solution with Excel Solver - Example 1 9 minutes
Optimal Solution with Excel Solver - Example 2 7 minutes
Optimal Solution with Excel Solver - Example 2 Solution 4 minutes
Case Exercise: "Make vs. Buy" Decision (A Computer Gaming Company) 4 minutes
Make vs. Buy Decision: LP Formulation 9 minutes
Make vs. Buy Decision: Excel Solution Part 1 (Set Up the Problem) 12 minutes
Make vs. Buy Decision: Excel Solution Part 2 (Using Excel Solver) 4 minutes
Congratulations on Finishing the "Optimization for Decision Making" Course 3 minutes
Carlson School of Management: Master of Science Program in Business Analytics (MSBA) 2 minutes

2 readings Total 20 minutes

Carlson School of Management: MSBA Program Website 10 minutes
Management Information Systems (MIS) Research Center 10 minutes

2 assignments Total 120 minutes

Module 4 Graded Exercise: A Medical Device Example 60 minutes
Module 4 Practice Exercise: Calmetal, a Manufacturing Firm Example 60 minutes

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Instructor

Instructor ratings

(32 ratings)

Soumya Sen

University of Minnesota

11 Courses 51,749 learners

Offered by

University of Minnesota

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Reviewed on May 19, 2023

I love the calmness and the fact the course was detailed and concise as possible. Professor Soumya Sen is a great teacher.

Reviewed on May 15, 2021

Good teaching style with step by step guidance. Thanks for the connecting high school math (that I learned many years ago) to real life context. I look forward to the next course.

Reviewed on May 31, 2021

There are a lot of examples to work through and learn from which I find helps make the material easier to learn.

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