Courses:

• Lectures are "required", and we will keep track of attendance. What this means in terms of grades is that there is a small penalty for missing lectures. Note: Absences for the first two lectures do not count.
  • Missing more than 10 lectures: -4% of final average
  • Missing 7 to 9 lectures: -2% of final average
  • Missing at most 2 lectures: +2% of final average
  • Signing attendance sheet for an absent student: -2% penalty per incidence
  • Leaving class shortly after signing in: -2% penalty per incidence
• Case study / Homework policy
  • Scoring less than 50% on total homework score: -5% of final average
  • Scoring less than 50% on total case score: -5% of final average

The subject is not graded on a curve. It is based on how well students master the material. The percentage of A's has varied substantially over the past three years.

Lectures are given twice weekly. Lectures include a mixture of presentation of material and interactive exercises. Participation is encouraged, but not required. Attendance will be taken at each lecture. Students should sign their name (and only their name) next to their printed name on the attendance sheet.

There are no lectures on exam days.

Homework is an essential tool for learning class materials. All problem sets can be done in groups of two. Problems vary from routine exercises that help reinforce the basics to more challenging problems that require insight into the models and algorithms. Except when stated otherwise, a homework set will be due every Thursday by 4:30 PM.

Each homework will have a cover sheet. The cover sheet needs to be attached, filled out and stapled to the homework assignment. Homeworks without a cover sheet will lose 10% of the total points for that assignment. The cover sheet expedites grading and gives the course staff valuable feedback that helps enhance future problem sets. We permit a 24-hour extension on one homework during the semester. In order to take advantage of this extension, an email needs to be sent to Professor Orlin at least three hours before the homework is due. The percentage of points earned on each problem set will correlate to a grade on a scale of 0-5 as follows:

This is our method of converting each homework to a letter grade A, B, C, D or F. As with letter grades, this grading scheme permits students to receive full credit without having to get every detail correct. It applies to all homework assignments, including both the Microsoft® Excel and the non-Microsoft® Excel assignments. It does not apply to midterms, the final exam, or quizzes.

We drop your lowest homework score of the term.

At the end of the semester we add up the converted grades (minus the one dropped) and give this value a 15% weighting towards the final grade.

Examinations help us to measure how you and the rest of the class are mastering the material and skills of the subject. Exams are given in the evening. Our suggested method for you to prepare for exams is for you to review your homework sets and attend the review session. Please see the course calendar for these dates. If you have conflict on an exam date please email us no later then 4 weeks prior to the exam.

Recitations are a critical part of the learning process. These weekly sessions last 90 minutes, and start with a 15 minute quiz. The purpose of the quiz is to encourage students to keep current with the course materials and to encourage students to review lecture materials so that they can follow the recitation better. In general, the quiz will be based on the homework set that is due prior to the recitation. The first quiz is based on the lecture material of the first week.

Following the quiz, a set of problems covering the material of the most recent week will be worked through. These problems are similar to HW problems and are often taken from old homeworks. The final part of the session will include group problem solving on more challenging problems. Attendance is mandatory at all recitations. The grade for recitation will be out of 20 points, 5 points for attendance and participation and 15 points for grades on the quizzes.

This year there will be four recitation sections: two on Thursday night, one on Friday morning and on Friday afternoon. Juniors and seniors who plan on going on interviews are encouraged to attend the Thursday night classes. We do not view interviews as excused absences. Athletes who often have games should attend the Friday recitations.

We drop your lowest recitation score.

There is no recitation on weeks with an exam.

This year, we are introducing a computer-based case study. The case study has weekly components that must be turned in individually. The assignments for the case study treat a "diet problem" from multiple perspectives, most of which involve the use of Microsoft® Excel Solver. The final assignment is a consultant's report based on what has been learned over the previous assignments. The deliverables for this part of the course should be presented in a professional manner, similar to the examples that we provide. The second to last lecture, we will have a class wide discussion of the case study and talk about extensions. More information on this will be given in a separate document.

We do not drop any of the case study scores.

For each day a case assignment is late, 5% will be deducted from the total score on that assignment.

In the tutorials section, there are tutorials that are meant to refresh the basics of what you need to know for lectures, and to reinforce skills that students may not fully grasp when first seen in lecture.

Professor Orlin joined the MIT Sloan faculty in 1979, first taught 15.053 in 1980, and has been teaching it regularly for the past 10 years. He enjoys fine tuning the syllabus and the lectures and enjoys adding new features to the class. This year, the Microsoft® Excel homeworks based on a personalized diet problem is the new addition to the class. (He developed it jointly with Mike Metzger.)

In research, Professor Orlin works on developing efficient optimization algorithms. He has developed improved solution methodologies for problems in airline scheduling, railroad scheduling, logistics, network design, telecommunications, inventory control, marketing, and computational biology. He is especially interested in developing techniques that obtain high-quality solutions in a short amount of computation time. Together with MIT Sloan colleague Thomas L. Magnanti and long-time collaborator Ravindra K. Ahuja, he has written the award-winning text Network Flows: Theory, Algorithms, and Applications (Prentice Hall, 1993).

On a personal note, Professor Orlin enjoys watching TV shows with his 15-year-old daughter, including Heroes, Veronica Mars, and Family Guy. He also regularly watches the Daily Show.

Mike Metzger is a third year PhD student at the Operations Research Center. Mike arrived at MIT in 1999 as an undergraduate, received his bachelors degree in Course 6 and Course 15 in 2003, and his masters in Course 6 in 2004. He has a long fond history with 15.053. He was a student in the class in the fall of 2001 with Professor Orlin as the lecturer. (Sloan used to offer one section of 15.053 each term.) He has TA'd 15.053 for the past three years. He was voted Sloan TA of the year by last year's class. His main area of research is probabilistic modeling and improving educational methods for undergraduates. An avid tennis fan, Mike has attended the past 10 consecutive U.S. Opens, and he hopes to attend Wimbledon. His favorite TV shows are Yes Dear, Six Feet Under, and anything on the Game Show Network. He also loves to travel, and considers a month to be successful if he spends at least one weekend on the beach in Florida or in the casinos of Las Vegas.

Hamed Mamani is a fourth year PhD student at the Operations Research Center. He received his bachelor's degree in Industrial Engineering in 2003 at Sharif University. His main research area is operations and supply chain management with a special focus on healthcare systems. Hamed has been a TA for about 4 years back while he was an undergraduate student. His hobbies include movies (mainly from 70s) and any sport!

Murali Swamy is a 2007 MBA candidate at the Sloan School of Management. Prior to coming here, he was an independent consultant working with companies in High Tech and Retail solving problems in operations and supply chain management. Murali was a TA for a sophomore course in Dynamics at the University of Maryland, College Park, where he got his Masters degree in Mechanical Engineering. Murali is a cricket nut. In India, where he was born, he played regularly. These days he follows the game internationally via Cricinfo. He loves watching movies, playing squash and skiing.