Instructor: | Marcel Oliver |
Email: | m.oliver@jacobs-university.de |
Phone: | 200-3212 |
Office hours: | We, Th 10:00 in Research I, 107 |
TA: | TBA |
Lectures: | Tu 8:15-9:30, Tu 9:45-11:00 in the Research I Lecture Hall |
Homework: | 30% |
Midterm Exam: | 30% |
Final Exam: | 40% |
05/09/2016: | Introduction, Simple linear programming problems |
05/09/2016: | Linear Programming: Graphical Solution R. Larson, Elementary Linear Algebra, Chapter 9.2 |
12/09/2016: | Review: Underdetermined linear systems Old class handout on Gaussian elimination |
12/09/2016: | Standard form of an LP problem, slack variables, geometry of feasible region |
19/09/2016: | Solving a simplex tableau Class notes, Section 1 |
19/09/2016: | Introduction to Pyomo Modeling Ipython notebooks as shown in class |
26/09/2016: |
Sensitivity, shadow prices, and duality Van Roy and Mason, Section 4.1 |
26/09/2016: | Another simplex method example;
weak duality theorem Van Roy and Mason, Section 4.2.1 |
29/09/2016: | Duals in a transportation network Class notes, Section 3 (start) |
10/10/2016: | Strong Duality Theorem Class notes, Theorem 2 with proof; Network Optimization I: Transportation Problem Hillier and Lieberman, Chapter 8 |
10/10/2016: | Network Optimization II: Shortest path,
minimum spanning tree, and
maximum flow problems; linear programming formulation for
shortest path and maximum flow Hillier and Lieberman, Sections 9.1-9.5 (focus on LP formulation of these problems) |
17/10/2016: | Network Optimization III: Network duals and
their interpretation;
Minimum cost flow problem Hillier and Lieberman, Section 9.6 |
17/10/2016: | Network Optimization IV: Pyomo
implementations; arbitrage detection. Project management, critical path, project crashing Hillier and Lieberman, Section 10.3, 10.5 |
TBA: | Midterm Exam |
24/10/2016: | Two player zero sum games
(Van
Roy and Mason, Section 4.4) Arbitrage detection (example graph, code) |
24/10/2016: | Dynamic Programming I: Shortest path
revisited, "Local Job Shop" problem Hillier and Lieberman, Section 11.1, Section 11.3 Example 4 |
07/11/2016: | Dynamic Programming II: Distribution of
effort problem, decisions under uncertainty, review of Bayes'
rule Hillier and Lieberman, Section 11.3 Example 2, Sections 15.2-3 |
07/11/2016: | Dynamic Programming III: Decision trees;
turning nonlinear programs into dynamic programs Hillier and Lieberman, Section 15.4; Exercise 11.3-20 |
14/11/2016: | Dynamic Programming IV: The value of
information; "Hit-and-Miss Manufacturing Co." as a further example
of decision analysis Hillier and Lieberman, Section 15.3 (finish); Section 11.4 Example 6 |
14/11/2016: | Nonlinear Programming I: Basic examples;
using Ipopt as a solver for linear and nonlinear programming
problems Hillier and Lieberman, Section 13.1 |
21/11/2016: | Nonlinear Programming II: Separable and
fractional programming - converting nonlinear programs into
linear programs Hillier and Lieberman, Sections 13.8 and 13.8 |
21/11/2016: | Nonlinear Programming III: Review of unconstrained smooth optimization, Lagrange multipliers, introduction to the KKT conditions |
28/11/2016: | Nonlinear Programming IV: Quadratic programming; Integer programming in Pyomo |
28/11/2016: | Inventory Theory I: EOQ model and variants Hillier and Lieberman, Sections 19.2 and 19.3 |
05/12/2016: | Inventory Theory II: Deterministic
periodic review model, serial two-echelon model Hillier and Lieberman, Sections 19.4 and 19.5 |
05/12/2016: | Inventory Theory III: EOQ with stochastic
demand, stochastic single-period model for perishable products Hillier and Lieberman, Sections 19.5 and 19.6 |
TBA: | Final Exam |