Coursera - Discrete Optimization [repost]

Discrete Optimization - section of mathematical programming. Combinatorial optimization problems can be solved by the methods of discrete programming. One of the main methods of solving discrete programming problems are the branch and bound and dynamic programming. On these and other methods described in the course.

About the Course
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 and helps Treatments Scientists Understand the Fundamental fabric of life, control Complex Chemical reactions, Design and 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.

Course Syllabus
The course has an Open format. At the start of the course all of the assignments and lectures are available and each student is free to design their own plan of study. The assessments in the course consist of five programming assignments and one extra credit assignment. In the programming assignments, students experience the challenges of real world optimization problems such as selecting the most profitable locations of retail stores (warehouse location) and the design of package delivery routes (vehicle routing). The class community is an important aspect of this course and students are encouraged to collaborate and help each other in the completion of the assignments.