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Johns Hopkins University | EN.550.666

Combinatorial Optimization

3.0

credits

Average Course Rating

(4.64)

The main goal of this course is to introduce students to combinatorial optimization techniques. The first part of the course will focus on combinatorial algorithms for classical problems. The next part of the course will show how polyehdral theory can be used to deal with combinatorial optimization problems in a unifying manner. Familiarity with linear programming and algorithms desirable but not strictly required. Recommended Course Background: Linear Algebra.

Fall 2012

(4.56)

Fall 2013

(4.55)

Fall 2014

(4.8)

Fall 2012

Professor: Rico Zenklusen

(4.56)

Students said the professor is a good lecturer and explained the theorems well. The material is relevant to many other fields of research. The downsides were that homework was very time-consuming and the solutions were not posted. Students suggested posting homework solutions or other solved problems for study purposes. The course covers a broad range of topics and the workload is heavy. Students would greatly benefit by having some background in linear algebra before taking this course.

Fall 2013

Professor: APPLIED MATHEMATICS AND STATISTICS

(4.55)

Students praised this course for its interesting subject matter and appreciated how the instructor taught the materials in a clear and logical manner. However, students felt the course had an uneven pacing, with some students saying the course went slowly through some topics and then breezed through others. Suggestions for improvement included grading the course’s homework assignments and count it towards students’ final grades. Prospective students should know that the course required students to have a good work ethic and discipline as homework assignments ha to be completed, despite being ungraded. These homework assignments prepared students for lectures and other assignments.

Fall 2014

Professor: Amitabh Basu

(4.8)

Students praised this course for presenting challenging and useful concepts in matrices. Perceived issues with the course were few; however, one student found that the exams weren’t that chal enging. Suggestions for improvement varied; for example, one student wanted the exams and homework to be more chal enging while another student wanted the class size reduced. Prospective students should know that students thought the course was focused on matrix concepts and that having a background in linear algebra was helpful. 18