Wiki page, MVE166 / MMG631 Linear and integer optimization with applications: Lectures plan

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2022-11-17T12:52:01+01:00

Preliminary plan for the lectures, including reading instructions from the book Optimization

Lecture # | Content | Chapters in the course book
1 | Introduction; course map; modelling optimization applications | 1, 2.1–2.5, 3
2 | Convexity and linear optimization | 2.4, 4.1
3 | A: Julia/JuMP and optimization solvers; computer exercise on linear optimization. B: Supply chain (Assignment 1) |
4 | Linear optimization: basic feasible solutions | 4.2–4.4, 4.8
5 | Linear optimization: the simplex method | 4.5–4.10, (7.1)
6 | Duality in linear optimization models | 6, (7.3, 7.5)
7 | Linear optimization: post-optimal and sensitivity analysis | 5.1–5.5, (5.6)
8 | Integer linear optimization: modelling, applications, complexity | 13, 2.6
9 | Optimization of maintenance scheduling (Assignment 2) |
10 | Integer linear optimization: relaxations, bounds, the branch&bound algorithm | 14.1–14.3, 15.1–15.3
11 | Integer linear optimization theory and algorithms: good/ideal formulation, cutting planes, Lagrangean duality and relaxation | 14.4–14.5, 17.1–17.2, (17.3–17.4), 13.10–13.11, 15.4, (15.5)
12
13 | Integer linear optimization: (non-)convexity, local/global optimality, heuristics and approximation algorithms | 16, 8.3
14 | Network flows: linear optimization formulations | 8.1–8.2, 8.4, (8.5), 18.1–18.5, (18.6–18.7), 13.5
15
16 | Linear optimization formulations and algorithms for minimum cost network flows | 8.6–8.7
17 | Summary of the course or solution of an exam |