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 from 11:00 AM - 12:30 PM on Tuesdays and Fridays, 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. You can purchase the student edition from the bookstore for just over \$100 or, slightly cheaper, direct from the Mathworks here. 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
 Approximate Schedule 9/4: Introduction 9/6: One-dimensional optimization, sensitivity analysis 9/11: Multi-dimensional optimization, Lagrange Multipliers, shadow prices; HW1 distributed, Dataset 9/13: Intro to and plotting in Matlab 9/18: Optimization using Newton's Method and variants; HW2 distributed 9/20: Types of optimization, linear programming; HW1 due 9/25: Linear programming and fair division; HW3 distributed, cake_division.m, fair_division.m 9/27: Network flows and linear programming; HW2 due 10/2: The simplex algorithm; Midterm project 1 distributed 10/4: Duality and complementary slackness; HW3 due 10/11: Dual prices, integer programming 10/16: Branch and bound algorithms; HW4 distributed 10/18: Graph models, max flow and min cut; Midterm Project 1 due 10/23: Bipartite graphs, matchings, selection problems; HW5 distributed 10/25: Scheduling problems, critical path method, Gantt charts; HW4 due 10/30: Finite-state machines, transition diagrams; HW6 distributed 11/1: Iterations matrices, eigenvectors, power iterations; HW5 due 11/6: Stochastic Matrices, Markov Chains; Midterm Project 2 distributed 11/8: Intro to statistics, central limit theorem; HW6 due 11/13: Monte-Carlo Integration, pseudorandom numbers 11/15: Monte-Carlo Simulation, Strategy 1 code, Strategy 2 code 11/20: Binomial and Poisson distributions; Midterm Project 2 due, HW7 distributed. 11/27: Recurrence Relations and Generating functions; HW8 distributed 11/29: Logistic Maps and Predator-Prey models; HW7 due 12/4: Logistic Functions and Lotka-Volterra models 12/6: Conservation laws and fluid dynamics; HW8 due 12/13: No class, but final projects due at noon