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METHODS

The operations research analyst has a wide variety of methods available for problem

solving. For mathematical programming models there are optimization techniques

appropriate for almost every type of problem, although some problems may be difficult

to solve. For models that incorporate statistical variability there are methods such asprobability analysis and simulation that estimate statistics for output parameters. In most

cases the methods are implemented in computer programs. It is important that at leastsome member of an OR study team be aware of the tools available and beknowledgeable concerning their capabilities and limitations.

In this section we include a number of topics that relate to the methods of operations

research. The contents of this section are arranged by problem type. This Methods

section includes the documentation for the teaching add-ins.

Add Teach TheAdd Teach add-in allows the user to install and

remove add-ins in theTeach OR

collection withoutusing theAdd-in command of the Tools menu. With theadd-in installed, Teach appears on the main Excel

menu. Selecting theAdd Teach item presents a dialog

that installs or removes add-ins with a click of thebutton. The add-in also opens demonstration

workbooks that illustrate the operations of the TeachOR collection.

Linear

Programming

We provide three units to demonstrate and teach linear

programming solution algorithms.

Primal Simplex Demonstrations areimplemented usingFlash to illustrate basicconcepts of the primal simplex technique.

The Teach Linear Programming Add-in

implements three different algorithms for

solving linear programming models.

Network FlowProgramming

We provide five units to demonstrate and teach

network flow programming solution algorithms.

The Teach Network Add-in implements thenetwork primal simplex method for both pure

and generalized minimum cost flow problems.

A graphical demonstration usingFlashillustrates and contrasts algorithms for finding

the minimal spanning tree and shortest path

tree.

The Transportation primal simplex method is

http://www.me.utexas.edu/~jensen/ORMM/methods/unit/teach_or/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/linear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/linear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/network/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/network/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/linear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/linear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/network/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/network/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/teach_or/index.html

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METHODS

implemented in the Teach Transportation Add-

in.

A graphical demonstration usingFlash

illustrates the network primal simplex method.

IntegerProgramming

The Teach IP Add-in implements three methods for

solving linear integer programming problems. The add-in provides demonstrations and hands-on practice for

the branch and bound method, the cutting plane method

and Benders' algorithm.

Nonlinear

Programming

The Teach NLP Add-in demonstrates direct search

algorithms for solving nonlinear optimization

problems.

Dynamic

Programming

The Teach Dynamic Programming Add-in has features

that allow almost any system appropriate for dynamic

programming to be modeled and solved. The programincludes both backward recursion and reaching.

http://www.me.utexas.edu/~jensen/ORMM/methods/unit/integer/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/integer/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/nonlinear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/nonlinear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/dynamic/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/dynamic/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/integer/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/integer/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/nonlinear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/nonlinear/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/dynamic/index.htmlhttp://www.me.utexas.edu/~jensen/ORMM/methods/unit/dynamic/index.html