|Back to CS Home Page|
Computer Science Course Information
|Course No.||CIS 786||Sections||101|
|Prerequisite(s)||Introduction to probability (Math 333 or equivalent) and introduction
to algorithms (CIS 435 or equivalent).
|Instructor|| James Calvin
|Instructor Office Hours||
|Topics||Tentative Course Outline
1. Linear programming; formulation and examples; simplex method; duality.
2. Integer programming; applications, heuristic methods.
3. Stochastic dynamic programming; Markov decision processes; optimal routing.
4. Global optimization, randomized algorithms; simulated annealing; evolutionary al gorithms.
5. Methods based on stochastic models; average-case analysis.
6. Optimization with noise-corrupted function evaluations.
7. Simulation-based optimization.
|Text Book(s)||Sections of the course will be based on chapters of Introduction to
Algorithms (Second Edition) by Cormen, Leiserson, Rivest, and Stein; MIT Press
and McGraw Hill, ISBN: 0262032937. Other parts will rely on class handouts. If
you do not have the book, you do not need to buy it.
|Time & Place||Tuesday 6:00 PM - 9:05 PM, Culm Lect # 2|
There will be biweekly problem sets which count for %100 of the grade.
Optionally, a project can substitute for the last two problem sets. The purpose of
the project is to propose and analyze an algorithm or investigate an optimization
problem that arises in a eld of interest to the student.
Academic Honesty: It is every student's responsibility to understand and adhere to the provisions of the academic honor code.
Students will be consulted regarding any changes to the syllabus.