15.053:    Optimization Methods
                      in Business Analytics

Instructors:   Tom Magnanti and Jim Orlin

 

 

 

 

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Syllabus

Subject reviews:
    Spring 2021
    Spring 2022

15.053 Project

 

OCW (2013)

 

15-2 Major

 

 

This website is for MIT students who want to learn more about 15.053, Optimization Methods in Business Analytics.  Welcome!

15.053 is an introduction to optimization models and methods. 

1.     REST

2.     Core subject in  15-2 major and minor in business analytics.

3.     Elective in the minor in Statistics and Data Science.

4.     Satisfies optimization requirement in  6-14 major: Computer Science, Economics and Data Science.

 

Instructor:   Tom Magnanti

Tom Magnanti

Thomas Magnanti is an Institute Professor and a Professor of Operations Research at the MIT Sloan School of Management.

Home page.

Wikipedia page

 

Instructor:   Jim Orlin

James Orlin is the E. Pennell Brooks (1917) Professor in Management and a Professor of Operations Research at the MIT Sloan School of Management.

Home page.

Wikipedia page

 

 

Course content and goals

Optimization is an important subfield of operations research and business analytics (see below).  The field of optimization is often referred to as "prescriptive analytics."   Its purpose is to determine the best possible solutions for an organization.  This contrasts with "predictive analytics" whose purpose is to identify the likelihood of future outcomes based on historical data.

Optimization models have been of great value within business, engineering, as well as science. In 15.053, students will see applications of optimization modeling in logistics, manufacturing, statistics, machine learning, transportation, game theory, marketing, project management, and finance.

In 15.053, students learn how to express optimization models conceptually (on paper) and then translate these models to a computer using either spreadsheet software (such as Excel) or an algebraic modeling language (such as JuMP, which is written in the Julia language.)  After translating the model so that it can be understood by a computer, students can use state-of-the-art solvers such as Gurobi to obtain an optimal solution.    

Students learn several types of optimization modeling, including linear programming, network optimization, integer programming, and nonlinear programming.  Students also learn basic solution methodologies for these optimization models.

There is a substantial group project for 15.053, in which student teams select and solve an optimization problem of their choice.  Examples of projects from past years are given below.

Our goal in 15.053 is to help students develop an "optimization mindset".  We want students to look out at the world and see optimizations problems everywhere, and to recognize when these problems can be modeled, analyzed, and solved.

The "semester at a glance" for 15.053 from spring 2022 is given here.

 

What are operations research and business analytics?

The field of operations research (O.R.) began in the 1940s as mathematicians developed techniques for practical problem solving. Today, O.R. is the application of advanced analytical methods to help make better decisions. Closely connected to O.R., analytics is the scientific process of transforming data into insight for making better decisions. Both offer exciting ways to apply math methods to real-world situations and everyday decision making.

 

Student's reviews of 15.053

Here are student evaluation reports of 15.053 from Spring 2021
and Spring 2022.

The following is excerpted from an interview with an MIT alum.

From https://cubscentral.wordpress.com
/tag/austin-filiere/

҉     I've enjoyed my time at MIT and Sloan tremendously. My favorite business course has been Optimization Methods with Professor Orlin. Together, my friends and I were able to do a project where we used Python code to build a simulation of a Red Sox lineup. Adopting an optimization mindset and seeing how businesses find the most efficient ways to do things made this course one of the most applicable for me.

Austin Filiere.   MIT '18.  
Drafted by Chicago Cubs in 2017.  
(From an article in Poets and Quants.)

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Applications and the course project.

Optimization models and methods can be applied to management, engineering, and science, and more.  Within 15.053, we show how to optimize problems within machine learning and statistics, sports analytics, finance, operations, marketing, as well as other domains.

Students have an opportunity to apply what they learn in 15.053 in their course project.  Students often choose projects of importance to MIT or of personal interest to themselves.

Here are some examples of  past 15.053 projects .

 

INFORMS: The Institute for Operations
Research and the Management Sciences

INFORMS, the professional society for Operations Research and Business Analytics, defines Analytics as "the scientific process of transforming data into insights for making better decisions."

You can learn more about operations research and analytics at the "Student Union" website sponsored by INFORMS.

 

 

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