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matlaboctavelinear-programmingglpk
Cherry
Cherry

Reputation: 1041

Difference between simplex method and revised simplex method in GLPK solver

I am trying to solve an LP minimization problem with glpk solver in octave for large data. my constraint matrix is having 1000 or more rows. I am confused about using that lpsolver=1 option of glpk. I do not the difference of using that or not. Will I get the same result if i use that option or not? Any help regarding this will be appreciated.

Upvotes: 1

Views: 1655

Answers (1)

anquegi
anquegi

Reputation: 11522

If you look at the octave help you will find this

lpsolver (default: 1)

Select which solver to use. If the problem is a MIP problem this flag will be ignored.

1

    Revised simplex method.
2

    Interior point method.

So really in only differs on terms of efficiency in certain problems, if you look for a comparision for example in Wikipedia you will find:

The current opinion is that the efficiency of good implementations of simplex-based methods and interior point methods are similar for routine applications of linear programming.[14] However, for specific types of LP problems, it may be that one type of solver is better than another (sometimes much better), and that the structure of the solutions generated by interior point methods versus simplex-based methods are significantly different with the support set of active variables being typically smaller for the later one.[15]

LP solvers are in widespread use for optimization of various problems in industry, such as optimization of flow in transportation networks

And also in this case it is ignored

If only some of the unknown variables are required to be integers, then the problem is called a mixed integer programming (MIP) problem. These are generally also NP-hard because they are even more general than ILP programs. In this case this parameter is ignored

Upvotes: 2

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