MVE165/MMG631, Linear and integer optimization with applications, 2017/18

Latest news

Welcome to the course!

General information

Teachers

Ann-Brith Strömberg
Examiner and lecturer
Professor, Mathematical Sciences
Email: anstr@chalmers.se, Tel: 772 5378, Room: L2087

Quanjiang Yu
Exercise assistant and assignment advisor
Ph.D. student, Mathematical Sciences
Email: yuqu@chalmers.se, Tel: 772 1094, Room: L2033

Edvin Åblad
Exercise assistant and assignment advisor
Industrial Ph.D. student, Mathematical Sciences and Fraunhofer-Chalmers Research Centre for Industrial Mathematics
Email: edvind@chalmers.se, Tel: 772 4275 or 772 1094, Room: L2033,

Course literature


The course (i) and exercise (ii) books are available in both Swedish and English and sold by Cremona.
Complementary material (iii) (mainly from the book Optimization in Operations Research by R. L. Rardin; Prentice-Hall, 1998) will be handed out during the course.

Course plan and contents

Preliminary course plan (180313) including time plan and deadlines.
Lecture notes are published regularly under Latest news.

Recommended exercises—problem solving sessions (the list below is updated each week).
Note that there are two options each week for the problem solving sessions, of which you are typically assumed to visit at most one. Typically, Wednesday sessions are given by Edvin and Thursday sessions by Quanjiang.
Session Dates Topics Recomended Exercises Teacher exercises
1 21/3, 22/3 Mathematical modelling 3.1 b,c,d; 3.5, 3.10, 3.12, 3.15 3.1 a,e,f; 3.4, 3.6, 3.14
2 11/4, 12/4 Linear optimization and the simplex method
2.4, 2.6, 4.2, 4.6, 4.10, 4.11, 4.15 4.5, 4.13
3 18/4, 19/4 Sensitivity analysis and duality theory
5.1, 5.5, 6.6, 6.8, 6.10, 6.15 5.4
4 25/4, 26/4 Integer linear optimization and the branch-and-bound algorithm 13.5, 13.6, 13.9, 15.6
(13.8, 13.15, 15.3, 15.12, 15.14)
example
5 2/5, 3/5 Cutting plane methods, minimal cover, Lagrangean duality
14.4, 14.8, 17.9
(14.1, 14.3, 14.6, 14.9, 17.8)
14.5, examples
6 9/5 Network optimization: minimum spanning tree and shortest path algorithms 8.10, 8.12, 8.17a (8.18, 8.38ab) examples
7 16/5, 17/5 Nonlinear optimization: convexity and the KKT conditions 9.8, 9.10, 11.4, (9.4, 11.6) 11.3

Computer exercises and software

Assignments


Assignment descriptions