Web Sites for Teaching Graduate Optimization

A Compendium of NP Optimization Problems, by Pierluigi Crescenzi at Università di Roma and Viggo Kann at Sweden's Royal Institute of Technology.

This has a tutorial on NP completeness, followed by the problem lists in categories, notably Graph Theory, Network Design, Sets and Partitions, Sequencing and Scheduling, and Mathematical Programming. The information is like the seminal book by Garey and Johnson, and an index makes it easy to find a particular problem.

InterTools, by Roberto Battiti at Università di Trento.

This contains interactive tools for discrete optimization algorithms. It takes your problem from a file, and e-mails the output to you. Currently, it has tutorials and code for Maximum Satisfiability, Maximum Clique, and Graph Partitioning.

Materials by Robert J. Vanderbei at Princeton University.

This has notes (pdf files) and Java applets to have the student solve problems interactively. While these reference his LP book, they can be used independently. You can also have students tested by using the same Java applets but submit their scores to you (by e-mail).

Mathematical Programming Glossary, by Harvey J. Greenberg at UCD.

This is a general resource for students to bookmark. See the LP Short Course for how one might use this for assigned reading. It also refers to some relevant bibliographies on the web.

Network Flows

The following are suitable for 5490 (and parts of 4450)

1. Algorithms and Networks, notes by R. Gibbens at Cambridge University (different notation and terms than OR, ps files).
2. Network Flows, by R. Chandrasekaran at University of Texas at Dallas (extensive notes, pdf files).
3. Network Optimization, by M.A. Trick at Carnegie Mellon University (brief intro).
4. Network Simplex Method Pivot Tool, by Bob Vanderbei at Princeton University.
5. OR-Notes, by J.E. Beasley at Imperial College (intro).
6. Practical Aspects of Network Modeling, by D.R. Shier and J.P. Jarvis at Clemson University (terms and examples).

Neural Nets, by Kevin Gurney at University of Sheffield.

This is a book that you can see in html or postscript. There are 10 chapters, introducing the threshold logic unit (TLU), learning rules (viz., delta, backpropagation), associative memory (Hopfield nets), self-organization (Kohonen nets), and a few perspectives.

Test Problems

OR-Library, by J E Beasley at Imperial College.

MIPLIB, by Robert E. Bixby at Rice University.

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