MATH 451(b) Nonlinear Optimization — B
- Faculty
- Mathematics
- Last listed
- 1974–75
No longer offered. It’s in Waterloo’s scanned calendars from 1968–69 to 1974–75; the 1995–96 to 2023–24 calendars are on ucalendar.
Recent mathematical programming algorithms not requiring differentiability or continuity will be presented with the stress on practical implementation. Topics will include the Simplex and Complex algorithms, Powell’s conjugate direction method, difference approximations to differentiable methods. Computational aspects will include evaluating gradients by difference methods, reliability of answers, stopping criteria, and problem formulation. Applications will be given to problems such as warehouse utilization and automated machine controls industry. Recommended for students interested in operations research, industrial engineering, computer science and for those wishing to pursue graduate courses in mathematical programming. 2 hours lectures, one term Prerequisite: M45la
As printed in the 1972–73 to 1974–75 calendars, read by OCR; the scanned page is the original.
Discussed on r/uwaterloo
One post or comment in 1 thread mentions MATH 451, May 2019 to December 2024. Quoted word for word, newest first; each reply sits under the post and the comment that started its branch. Search r/uwaterloo for newer posts.
Spring 2019
Most useful Mathematical Finance courses? 10 points, 7 comments
“Kinda feel like taking mathematical finance, but I don't want to take all the lame courses. Plus I'm cs/bba and friend tells me I'd need to take an extra 6A term to get it all done - I'm not down for …”
u/XDDD_unemployed: “… For pure math 450/451, they are not obvisouly useful, but you need them for deeply understanding stochastic calculus, which is the main tool for derivative pricing/financial mathematics.”
Check it elsewhere
In the scanned calendars
How it read in each calendar from 1968–69 to 1974–75, newest first. The text is OCR of the scanned pages; years whose wording matches are shown once, from the clearest scan. Each year links to its page on uwloo and to that page of the scanned PDF.
1972–73 to 1974–75 3 calendars
Recent mathematical programming algorithms not requiring differentiability or continuity will be presented with the stress on practical implementation. Topics will include the Simplex and Complex algorithms, Powell’s conjugate direction method, difference approximations to differentiable methods. Computational aspects will include evaluating gradients by difference methods, reliability of answers, stopping criteria, and problem formulation. Applications will be given to problems such as warehouse utilization and automated machine controls industry. Recommended for students interested in operations research, industrial engineering, computer science and for those wishing to pursue graduate courses in mathematical programming. 2 hours lectures, one term Prerequisite: M45la
1971–72 1 calendar
Another title: Non-Linear Optimization(a) Classical Methods(b) Sequential Optimization 2 Linear Programming: (Theory, Applications, and Related Topics)(a)(b), probably a different course under the same number (or a misread scan).
Discrete functions; continuous functions of n variables. Quadratic forms; convex functions. Equality constraints; Langrange multipliers and generalizations. Inequality constraints: Kuhn-Tucker theorem. 2 hours lectures.
Gradient methods; recent sequential optimization methods; direct search methods; application to the solution of equation and non-linear regression analysis. 2 hours lectures.
Preliminaries, convex sets, geometric motivation for the Simplex Algorithm. Simplex Algorithm. Revised Simplex Algorithm. Degeneracy. Duality Theory. 2 hours lectures.
Transportation Problem. Shortest Path Problem. Primal Dual Algorithms. Maximum flow problems, Max-Flow Min-cut Theorem, Ford-Fulkerson Labelling Algorithm. Assignment Problems. Transshipment Problem. Capacitated Transportation Problem. Bounded Variables. Dual Simplex Algorithm. Post-optimal analysis (parametric programming, sensitivity analysis, etc.). Discrete Linear Programming. Branch and Bound Algorithms. The Travelling Salesman Problem. Integer Programming. Cutting Plane Methods. 2 hours lectures.
1968–69 to 1970–71 3 calendars
Titled Optimization.
Discrete functions; continuous functions of n variables. Quadratic forms; convex functions. Equality constraints; Lagrange multipliers and generalizations. Inequality constraints; Kuhn-Tucker theorem. Steepest descent and gradient methods. Fibonnaci search, successive approximations, simplex method and other techniques. Applications to the solution of equations and non-linear regression. 2 hours lectures.