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Computer Science Course Information

Level >Graduate >FALL_2005 >List >


Course No. CIS 786
Sections 101
Title Optimization
Course Website
Prerequisite(s) Introduction to probability (Math 333 or equivalent) and introduction
to algorithms (CIS 435 or equivalent).
Instructor James Calvin
  • Office Room No. : GITC 4311
  • Office Phone : 973-596-3378
  • Fax : 973-596-5777
  • Email :
  • Website:
  • Lab : -
  • Instructor Office Hours
    Description None
    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
    Other Info Grading:
    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.

    Registrar's Website