Optimization technology is ubiquitous in our society. It schedules planes and their crews, coordinates steel production, and organizes the transportation of iron ore from the mines to the ports. Optimization clears the day-ahead and real-time markets to deliver electricity to millions of people. It organizes kidney exchanges and cancer treatments and helps scientists understand the fundamental fabric of life, control complex chemical reactions, and design drugs that may benefit billions of individuals. This class introduces discrete optimization and exposes students to some of the field’s most fundamental concepts and algorithms. It covers constraint programming, local search, and mixed-integer programming from their foundations to their applications for complex practical problems in scheduling, vehicle routing, supply-chain optimization, and resource allocation.

Sep 10, 2017

This is a fun and challenging course! Without a doubt the most challenging course I’ve ever done in Coursera!

I have a few suggestions for anyone who is considering starting this course:

1- You must be a skillful programmer and be comfortable with algorithm design, tree and graph structures, and recursion. Also, general knowledge of models is useful.

2- You have to have enough patience to watch loooooooong videos (but the professor teaches in pretty awesome and, at times, hilarious ways!)

3- You need to spend +15 hours per week on this course; the videos for each week are long, and each programming assignment will take a tremendous amount of your time!

4- Finally, you should be tough, not give up, and sometimes dare to write your code again from scratch after failure!

Amin F

Student

May 30, 2019

Exceptional coverage of optimization fundamentals. Learning of practical applied methods. Real university-level course, with no water down “data science”. Absolutely love it! Thank you, professor Pascal.

Student

Jul 22, 2017

Exceptional coverage of optimization fundamentals. Learning of practical applied methods. Real university-level course, with no water down “data science”. Love it! Thank you, professor Pascal!

Student

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Pascal Van Hentenryck

Professor

Bio

Pascal Van Hentenryck holds a Vice-Chancellor Strategic Chair in Data-Intensive Computing at the Australian National University and is the leader of the Optimisation Research Group at NICTA. Before that, he was a professor of computer science at Brown University for more than 20 years and a professor at the University of Melbourne. His main research interests are the design and implementation of optimization systems and their applications to complex problems. His current research projects focus on optimizing logistics and supply chains, energy, and disaster management. He has written five books for the MIT Press and built several optimization systems widely used in academia and industry. He received an NSF Young investigator award in 1993, a 2002 INFORMS Computer Society Award, two Honorary Doctorate Degrees from the University of Louvain and the University of Nantes, the Philip J. Bray Award for Teaching Excellence in the Physical Sciences at Brown University, and became a fellow of AAAI in 2009. He has given plenary talks at the main artificial intelligence and operations research conferences. Pascal has taught discrete optimization at Brown University, the University of Louvain, and now on Coursera for almost 20 years.

Dr. Carleton Coffrin

Professor

Bio

Dr Carleton Coffrin is currently a Los Alamos National Laboratory (LANL) staff researcher. He investigates how state-of-the-art optimization methods can benefit decision-support applications in power systems and disaster management. Before joining LANL in 2016, Dr. Coffrin conducted his Ph.D. studies at Brown University in the area of hybrid optimization for disaster management under Pascal Van Hentenryck and Russell Bent. Dr. Coffrin is passionate about optimization education and is proud to be involved with both Discrete Optimization and Modeling Discrete Optimization MOOCs.

Discrete Optimization
$49.00

Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming. Optimization technology is ubiquitous in our society. It schedules planes and their crews, coordinates the production of steel, and organizes the transportation of iron ore from the mines to the ports. Optimization clears the day-ahead and real-time markets to deliver electricity to millions of people. It organizes kidney exchanges and cancer treatments and helps scientists understand the fundamental fabric of life, control complex chemical reactions, and design drugs that may benefit billions of individuals. This class is an introduction to discrete optimization and exposes students to some of the most fundamental concepts and algorithms in the field. It covers constraint programming, local search, and mixed-integer programming from their foundations to their applications for complex practical problems in areas such as scheduling, vehicle routing, supply-chain optimization, and resource allocation.

ADDITIONAL DETAILS
Landing Page Discrete Optimization
Manufacturer The University of Melbourne
Category Educational Software
Availability In Stock
SKU crse:THkzKaBPEeWm9xJA1YXcWQ
GTIN

Now it’s time for the Yale University Law Student’s Toolkit!

Now time for Discrete Optimization!

Pascal Van Hentenryck

Bio

Dr. Carleton Coffrin

Bio