Course Information

Syllabus

The course meets in H+ block, from 1:30-2:45 PM on Tuesdays and Thursdays, in Room BP-5. My office hours are Tuesdays from 9:30-11:30 and Thursdays from 9:30-10:30, in Room BP-212.

Programming
The programming for this course can be done in any language that you choose. Matlab is probably the easiest to pick up if you are not familiar with any other. All Tufts students have access to Matlab in the ITS Computing Center @ Eaton Hall. A free alternative to Matlab is Octave. Other possibilities include using python with numpy/scipy/matplotlib. If you would like to use another option, please discuss this with me.

Matlab Resources
Schedule

  • 9/6: Introduction
  • 9/8: One-dimensional optimization, sensitivity analysis
  • 9/13: Multi-dimensional optimization, Lagrange Multipliers, shadow prices; HW1 distributed, HW1 data
  • 9/15: Intro to and plotting in Matlab
  • 9/20: Optimization using Newton's Method and variants; HW2 distributed
  • 9/22: Types of optimization, linear programming
  • 9/27: Linear programming and fair division; HW3 distributed
  • 9/29: Network flows and linear programming
  • 10/4: The simplex algorithm; Midterm Project 1 distributed
  • 10/6: Duality and complementary slackness
  • 10/11: Dual prices, integer programming
  • 10/13: Branch and bound algorithms
  • 10/18: Graph models, max flow and min cut
  • 10/20: Bipartite graphs, matchings, selection problems
  • 10/25: Scheduling problems, critical path method, Gantt charts; Midterm Project 1 due, HW4 distributed
  • 10/27: Finite-state machines, transition diagrams
  • 11/1: Iterations matrices, eigenvectors, power iterations
  • 11/3: Stochastic Matrices, Markov Chains; Midterm Project 2 distributed
  • 11/10: Intro to statistics, central limit theorem
  • 11/15: Monte-Carlo Integration, pseudorandom numbers
  • 11/17: Monte-Carlo Simulation, Strategy 1 Code, Strategy 2 Code
  • 11/22: Binomial and Poisson distributions, HW5 Distributed, Midterm Project 2 due.
  • 11/29: Recurrence Relations and Generating functions, HW6 Distributed
  • 12/1: Logistic Maps and Predator-Prey models
  • 12/6: Logistic Functions and Lotka-Volterra models
  • 12/8: Conservation laws and fluid dynamics
  • 12/13: No class, but final projects due