|
|
15.053 Optimization
Methods in Business Analytics Instructor: James B. Orlin |
|
Menu |
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.
James
Orlin is the E. Pennell Brooks (1917)
Professor in Management and a Professor of Operations
Research at the MIT Sloan School of Management. Course
content and goals In
15.053, we present modeling techniques in optimization that are known as
linear programming, integer programming, and nonlinear programming. Students can model optimization
problems using spreadsheet optimization -- e.g., Excel and Excel Solver (tutorial, spreadsheet) -- or
using an algebraic modeling language (Julia and JuMP). We also describe algorithms for
optimization problems as well as general purpose
heuristics. The
Spring 2019 syllabus of 15.053 is here. The subject evaluations for 2017 to 2019 are here. Here are (selected) student
comments from past years. 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. |
|
|
ÒIÕve 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. |
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. |
Among the past 15.053 projects
were:
á
optimizing hours for dining facilities
á
optimal radiation therapy
á
optimal allocation of freshmen to dorms
á
optimal allocation of gates at Logan airport
Business
Analytics and Operations Research
|
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. |
.