Handouts so far
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Syllabus
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Course requirements and marking policy
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Problem Set 1 and
the solutions for probset 1 and
comments from the marker.
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Problem Set 2;
Comments on problems (solutions were
handed out in class)
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Problem Set 3; and
MATLAB file pivotLP.m; and
the solutions for probset3 (please ask if you need clarification)
Two related MATLAB files are:
perturbset3prob2.m and
solnsset3prob2.m.
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Problem Set 4;
comments from the marker;
and
the solutions for Problem Set 4
MATLAB files:
probset4prob1p1.m,
probset4prob1p2.m,
simplex.m,
reg.m,
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Problem Set 5;
Three mat files for problem 1:
finddualprob1.mat,
finddualprob2.mat,
finddualprob3.mat.
Comments from the marker;;
*solutions* (thanks Tor!)
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Problem Set 6; (due thurs nov 10, midnight)
and
Solutions(Thanks Masoud!)
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Class Quiz
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Problem Set 7; (due Mon nov 21, midnight);
a MATLAB program for the matrix rounding and
the solutions, pdf file (Thanks Masoud again!)
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Practice Final (web only handout)
Another Practice Final (web only handout)
(Replace Prim's algorithm in problem 6 with one of the greedy
algorithms that we convered in class.)
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Problem Set 8; (due Thurs Dec 8, midnight);
solutions, and
solution MATLAB file
websites/links/announcements
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Course goal
To learn fundamentals of
optimization problems and the algorithms to solve them.
Coverage includes linear and nonlinear problems and discrete
and continuous problems.
Course time and location
Monday, Wednesday, Friday, 9:30-10:20AM, MC4059
Instructor
H. Wolkowicz
MC 6065
519-888-4567 ext. 35589
Office hours:
Mondays 3:00-4:00 and Thursdays 2:30-3:30.
AND extra hour: Tues Dec 13, 2:00-3:00
Teaching Assistant
Tor Myklebust
MC 5147,
519-888-4567 x33861
Office hour:
Fridays 2:00-3:00PM
Texts
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D. Bertsimas and J. Tsitsiklis,
Introduction to Linear Optimization,
Athena Scientific, 1997
(on 3 hour reserve)
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D. Bertsekas, Nonlinear Programming: 2nd Edition.
Athena Scientific, 1999, first 100 pages. Note: these pages
are available as a course handout available for purchase from
Campus
Graphics
Prerequisites
Mathematical background should include linear algebra, multivariate
calculus, and elementary graph theory. Knowledge of programming in C,
Fortran, Python or MATLAB (preferred) is also a prerequisite.
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