Office Hours: I have an open door policy.
Walk in my office every time you want and I will interrupt whatever I am doing.
In case you feel better having an appointment, arrange for one. Two important rules to talk to me:
1. Make sure you thought about the problem and have some analysis to offer together with your question
2. Make sure you can explain you problem or make the question in one-two sentences.
The tentative list of topics covered and the approximate time devoted to them is in the list
below. The order of presentation and coverage will likely
be
altered. Every effort will be made to make the material relate to the different
disciplines spanned by the students attending the class.
Introduction and motivation. Examples of problems: Investment Planning. Supply Chain. Batch plant scheduling. Refinery Operations. Resource allocation. Pricing. Budgeting. (~2 weeks)
Optimization Theory. Linear and mixed integer linear programming models. Applications to deterministic models (models without uncertainty) (~ 3 weeks)
Introduction to uncertainty. Review of Statistics. Decision Trees. Regret Analysis. (~ 3 weeks).
Two stage and multistage stochastic programming. Chance Constraints.(~3 weeks)
Financial Risk. Use of contracts and options (~3 weeks)
Special tools: genetic algorithms, simulated annealing, Montecarlo sampling, etc. (~2 weeks)
Homework: Only a few.
Grading System:
The final project(s) will be assigned by the instructor. It could consist of an individual project, a group project, or both, depending on the scope. Students are welcome to propose projects. The instructor will determine the need for Tests or Final exams based on student performance.
Some Rules:
Any student in this course who has a disability that may prevent him or her from fully demonstrating his or her abilities should contact the instructor personally as soon as possible so accommodations necessary to ensure full participation and facilitate his/her educational opportunities are discussed