Why the optimal point of Multi-objective size optimization in Hyperstudy came out only 1 point?
I am doing the multi-objective size optimization using Hyperstudy to get the optimal solution under my optimization problem.
But the problem that I faced now is the optimal point that came out from Model 3 is only 1 point and I do not know the reason behind that because when I set the same way to Model 2, just the numbers of node and element that are constrained that different. The optimal point from model 2 was not only one point. it came out more than that.
This is my objective and constraint in Model 3
And this one is the result of pareto front that I confused why the model3 have only 1 point.
Pareto from model3
Pareto front from model 2
I try to attach the model file but the size is too large (205 GB) So, I will snap the screen to show the way that I set in pdf file, the file .tpl that consist of variables from cost and variables of thickness in each ply and the result from report of Model 3 in the form of spreadsheet.
I struggle with this quite long, I try to find the point that I missed but I did not work out.
Thank you in advance.
Best Answer
-
Hello,
from the screenshots it is not obvious to point out what's wrong. As a first suggestion, and based on your different constraints, I'd recommend you to look at your scatters, to see how the points are distributed, and how they satisfy, or violate, the constraints. Having a single point can indeed be caused by an over constrained optimization problem.
Hopes this can help
Michael
1
Answers
-
Hello,
from the screenshots it is not obvious to point out what's wrong. As a first suggestion, and based on your different constraints, I'd recommend you to look at your scatters, to see how the points are distributed, and how they satisfy, or violate, the constraints. Having a single point can indeed be caused by an over constrained optimization problem.
Hopes this can help
Michael
1 -
Michael Herve_21439 said:
Hello,
from the screenshots it is not obvious to point out what's wrong. As a first suggestion, and based on your different constraints, I'd recommend you to look at your scatters, to see how the points are distributed, and how they satisfy, or violate, the constraints. Having a single point can indeed be caused by an over constrained optimization problem.
Hopes this can help
Michael
Thank you so much. I will check the point that you recommend and by the way this is the scatters from model 3
And this is the scatter from model 2
Thank you in advance.
0