OPTIMISATION
2
by Misha Rudnev
People who made various contributions to this course:
click on an image for more info:
Lectures:
Tuesday 14:00 (Physics LT Mott)
Wednesday12:10 (Bio Sci LT B37)
Alternative Problem Class/office
hour for people with clashes, etc:
Office: 2.10 Howard House, office
hour on Tuesday 12:10 or by appointment.
!!! OPT2 MATHS CAFE: Thursday at 2 PortaCabins 6, Friday at 1 PortaCabins 2) !!!
Course descriptions: Opt2
2011/12
HOMEWORK
Each homework
contains a set of problems, some/many of which are marked as optional.
These latter ones are not mandatory, but are worth looking at as some
of them may have exam cousins. You may decide which ones by looking at
past exams on Blackboard
Homework is to be handed in and picked up from the cell in a rack of
shelves in the lobby of the main Maths building.
Assignment
1 Due Wednesday Oct 19 Solutions
Assignment 2
Due Wednesday Oct 26
Solutions
Assignment 3
Due Friday Nov 4 Solutions
Assignment 4
Due Friday Nov 11 Solutions
Assignment 5 Due
Friday Nov 18 Solutions
Assignment
6 Due
Friday Dec 9 Solutions
Assignment
7 Due Wednesday Jan 18 Solutions
Assignment 8 Due Friday
Jan 27 Solutions
NOTES - HANDOUTS
Study through these sets of notes as parts of homework assignments!
"Mathematical methods of economics...by Joel Franklin (who taught me Optimisation)" Brief introduction and all the examples one can think of (read it now up to page 12, read further at least through page 14 later in the course; Arrow theorem Joel discusses is not a part of Opt 2 but read it anyway: its maths in Political Science.)
Applications
of Farkas: game theory, Markov matrices,
and finance
Unconstrained
extrema
Convex Functions
NEW: Some
applications of Cauchy-Schwarz inequality
Equality
constraints: Lagrange multipliers
Inequality
constraints: Kuhn-Tucker (Lagrange) conditions
EXAM REVISION MATERIAL
MEAN NOTE: I am against making
solutions of past exam papers available, and have never made them
available. Won't even under torture!
To see past exams' scripts, log into Blackboard.
LINKS (These are mostly similar course notes
in other Unis; bits and pieces can
certainly be useful, although notation, etc. can be diffrent)
Berkeley version of Optimisation
Princeton version of Linear Programming
Linear Programming
from UCLA
Another Online
Set of Lecture Notes
Berkeley Online
Simplex Tableau Solver : use it to check your Simplex Method
homework
Another Simplex
Method Tutorial
A very good Optimisation
Links Site
Optimisation for engineers Lecture
notes, UC Davis
Linear and Non-linear Optimisation Summary
and Terms Glossary
or search Google for more.
OTHER LINKS THAT I FIND VERY USEFUL:
Bristol Ice Rink