You are welcome @Chunyang
I noticed that question was posted at:
It would be helpful to be a little more explicit in that question/post; give some more context. Possibly add an example of what you have done so far. I think that will help readers to answer.
@Chunyang , if you download the example, all details are exposed. You will find that ep_GMP is an element parameter defined over the (predefined set) AllGeneratedMathematicalPrograms.
ElementParameter ep_GMP {
Range: AllGeneratedMathematicalPrograms;
}
More information about this subject of math program generation can be found at:
https://how-to.aimms.com/Articles/147/147-GMP-Intro.html
Thanks a lot @Gertjan! I have got it now. By the way, May I ask another question? How can I solve different scenarios within one run? I hope the AIMMS can change the initial data to another scenario automatically after solving a scenario.
@Chunyang , if you download the example, all details are exposed. You will find that ep_GMP is an element parameter defined over the (predefined set) AllGeneratedMathematicalPrograms.
ElementParameter ep_GMP {
Range: AllGeneratedMathematicalPrograms;
}
More information about this subject of math program generation can be found at:
https://how-to.aimms.com/Articles/147/147-GMP-Intro.html
In this article we will compare a multi-objective approach to separately solving single objectives.
Let’s take for an example a problem trying to find a healthy diet for a reasonable price. First let’s define our objectives:
- Minimize calories: I’m trying to lose some weight, so my healthy diet should be low in calories.
- Minimize price: A reasonable price means that it doesn’t have to be the absolute minimum, but should be within a close range.
Now, let’s use the multi-objective feature to solve.
Read more...
Can you tell me how to define the “ep_GMP ” in this article?