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Discrete Optimization

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.

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The University of Melbourne

Rating 4.8 based on 106 ratings
Length 9 weeks
Effort 8 weeks of study, 10-15 hours per week
Starts Jun 29 (last week)
Cost $49
From The University of Melbourne via Coursera
Instructors Dr. Carleton Coffrin, Professor Pascal Van Hentenryck
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Mathematics
Tags Computer Science Algorithms Math And Logic

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discrete optimization in 11 reviews

Discrete optimization is a quasi-self-paced programming course offered by the University of Melbourne through Coursera that is all about solving hard problems.

Discrete Optimization is an introduction to solving some of the most difficult problems in computer science.

Even if you're not currently interested in discrete optimization, halfway into the course you are likely to loose your sleep over thinking of how to optimally solve Travelling Salesman Problem with 33810 cities or optimally color a huge random graph.

Even though I did know nothing about optimization at the beginning, this course managed to teach me many important aspects of discrete optimization.

Discrete optimization turned out to be a very exciting, fantastic and engaging course.

This course would probably also make you a better programmer overall due to the assignments that require from you to constantly improve on your code (so its not only discrete optimization, in a way its code optimization as well).

A considerable part of the course is implementing some tough discrete optimization tasks which are evaluated competitively against other participants.

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time consuming in 7 reviews

It has really time consuming and challenging programming assignments, but I learned more than I have in a long while.

The assignments are tough and time consuming and super addictive.

If you have a background in maths and programming and are willing to settle for an 'ordinary' statement of accomplishment, it need not be so hard and time consuming at all.

The homeworks are hard, time consuming but very challenging.

Getting distinction is significantly more difficult and time consuming and will often require many iterations of work improving your first solutions.

The programming assignments are hard and time consuming but also very fun.

This level of freedom is great for students who want to work ahead but it may make it difficult to complete the course if you don't plan ahead because the programming assignments can be very time consuming.

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local search in 6 reviews

I like the instructor teaching approach and the evaluation system, the subject itself took me a lot of effort and i think the LNS technique should be teached just after local search.

Don't be surprised if you find yourself at 5:00 AM trying to squeeze a slightly better solution then what you currently have.The course covers a lot of material: constraint programming, local search heuristics and meta-heuristics, linear and mixed integer programming.

But it is much harder to find a class that discusses local search heuristics, and this class may be unique in its focus on actually solving very tough examples of classic DO problems "by any means necessary."

My keywords: branch and bound (knapsack); iterated greedy, CP, cliques (graph coloring); simulated annealing, k-opt, clustering, lin-kernighan heuristic (travelling salesman); MIP, nearest-neighbors, LNS (facility location); MIP with subtour elimination, lazy constraints, nearest-neighbors, greedy as initial solution, local search, cluster-first route-second (vehicle routing).

Discrete optimization opens with an introductory lecture series on the knapsack problem that lasts a couple of hours followed by three longer lecture series, covering constraint programming, local search and mixed integer programming.

Most of the times the classical approaches like Mixed Integer programming and Constraint Programming fail to provide solution in a reasonable time.But that's when you become of intuitive developing your own ideas/ heuristics.This course covers a lot of optimization concepts like dynamic programming, Constraint Programming ,Mixed Integer programming and Local search.Waiting for the next one!..

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most challenging in 6 reviews

Without doubt the most challenging courses I've ever done in coursera!

One of the most challenging and interesting sources among all that I've passed so far.

This was one of the most fun and most challenging classes I've taken in any format.

This is the most challenging and hardest course I've completed in Coursera =) The freedom in the PAs to choose our own algorithms make it very challenging.

Good Course, I had learn a lot of concept of optimization The most challenging course that I've ever enrolled in.

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pascal van hentenryck in 5 reviews

Prof Pascal Van Hentenryck’s explanations of the problems were top-notch and his enthusiasm was just contagious!

Last but not least, Professor Pascal Van Hentenryck is really a nice man, he is humorous and charming.

So far I have completed seven or eight courses on Coursera, and although I have enjoyed them all very much, Discrete Optimization by Pascal van Hentenryck is my absolute number one!!

Also, proffesor Pascal Van Hentenryck is an awesome lecturer and his explanations are short, clear and easy to understand.

Pascal Van Hentenryck is one of the top researcher in this field and he has some great pedagogy skills.

The professor, Pascal Van Hentenryck, is extremely energetic and passionate about the subject.

I am sure this is the best course out there to help students/Professionals to understand the complexity of the optimization problems specially designed and explained by Professor Pascal Van Hentenryck in his own hilarious style .

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vehicle routing in 5 reviews

The entire course grade is based on 5 programming assignments: the knapsack problem, graph coloring, traveling salesman, warehouse location and vehicle routing.

Amazing class, large real world problems in vehicle routing, warehouse location tackled as programming assignments.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Delivery Optimization Analyst $94k

Process Optimization Specialist $96k

Engineering Solutions - Discrete Controls Engineer $102k

Drilling Optimization Engineer 3 $105k

Optimization and Development Analyst $109k

In charge of operation and optimization $112k

Cloud Optimization Engineer $123k

Senior Plant Optimization $132k

Product Optimization Leader $134k

Capabilities & Optimization Manager $142k

Marketing Optimization Analyst $154k

Optimization Strategist 2 $174k

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Coursera

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The University of Melbourne

Rating 4.8 based on 106 ratings
Length 9 weeks
Effort 8 weeks of study, 10-15 hours per week
Starts Jun 29 (last week)
Cost $49
From The University of Melbourne via Coursera
Instructors Dr. Carleton Coffrin, Professor Pascal Van Hentenryck
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Mathematics
Tags Computer Science Algorithms Math And Logic

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