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C_Golen
Obsidian | Level 7

Is there any way to do Operational Research Application (Especially Nonlinear optimization problem)on SAS Enterprise Miner 15.x?

Thanks in Advance!

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sbxkoenk
SAS Super FREQ

Hello @C_Golen ,

 

I do not think so.

I think the Rigorous Constrained Optimized Binning for Credit Scoring is a a mixed-integer nonlinear programming (MINLP) formulation, but for the formulation of your own nonlinear optimization problem(s) you need SAS/OR (Operations Research) or SAS/IML (Interactive Matrix Language).

SAS/OR PROC OPTMODEL has a super-friendly AML (Algebraic Modeling Language) to specify your mathematical program.

Enterprise Miner is not really an option.

 

Kind regards,

Koen

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4 REPLIES 4
sbxkoenk
SAS Super FREQ

Hello @C_Golen ,

 

I do not think so.

I think the Rigorous Constrained Optimized Binning for Credit Scoring is a a mixed-integer nonlinear programming (MINLP) formulation, but for the formulation of your own nonlinear optimization problem(s) you need SAS/OR (Operations Research) or SAS/IML (Interactive Matrix Language).

SAS/OR PROC OPTMODEL has a super-friendly AML (Algebraic Modeling Language) to specify your mathematical program.

Enterprise Miner is not really an option.

 

Kind regards,

Koen

C_Golen
Obsidian | Level 7

Hi @sbxkoenk ,

 

I was thinking the same way. But I wanted to be sure. 

Sorry for late replying. 

Thanks Again!

C_Golen
Obsidian | Level 7

Hi @sbxkoenk 
I have an extra question due to your answer. Is there any way to add binary variable to MILP? In my situation i have to add a variable about whether weather is rainy or sunny.

 

Thanks in Advance agian

sbxkoenk
SAS Super FREQ

Hello @C_Golen ,

 

You can definitely add binary variables to your MILP.
For sure just one, 20 or 50 binary variables may be challenging!

 

Taken from :

SAS/OR® 15.1 User’s Guide
Mathematical Programming -- The Mixed Integer Linear Programming Solver

(2018)

https://support.sas.com/documentation/onlinedoc/or/151/milpsolver.pdf

 

[Extract]

It is important to realize that mixed integer linear programs are nondeterministic polynomial-time hard
(NP-hard). Roughly speaking, this means that the effort required to solve a mixed integer linear program
grows exponentially with the size of the problem. For example, a problem with 10 binary variables can
generate in the worst case 2**10 = 1,024 nodes in the branch-and-bound tree. A problem with 20 binary
variables can generate in the worst case 2**20 = 1,048,576 nodes in the branch-and-bound tree. Although it is
unlikely that the branch-and-bound algorithm has to generate every single possible node, the need to explore
even a small fraction of the potential number of nodes for a large problem can be resource-intensive.

 

Look in this document for 'binary' or 'binary variable' and you will find some example code where binary variables are part of the problem formulation.

 

Good luck,

Koen

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