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I am looking for code, that is inverse of optimization. Have variable combinations (and plot them) that gives response value in a boundary.

7 Ansichten (letzte 30 Tage)
For example
Y=3a+2b+5c-6a^2+7b^2
...is model. I want to have a, b, c combinations values that result in Y within -2 & +2. In addition, the subset of a, b, c must be in a given boundary i.e. -3<a<2, 4<b<7, 9<c<18 etc.
  2 Kommentare
Walter Roberson
Walter Roberson am 25 Jul. 2018
Is the question to determine all such values? There would be an indefinite number of such values if you permit floating point.
Biswanath Mahanty
Biswanath Mahanty am 26 Jul. 2018
I understand, there is an infinite number of plausible solution. However, I need to draw a surface plot, with adequate combinations.

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Akzeptierte Antwort

Walter Roberson
Walter Roberson am 26 Jul. 2018
Y = 200; %for example
N = 50;
av = linspace(-3,2,N);
bv = linspace(4,7,N);
cv = linspace(9,18,N);
[a,b,c] = ndgrid(av,bv,cv);
dy = 3*a + 2*b + 5*c - 6*a.^2 + 7*b.^2 - Y;
mask = dy > -2 & dy < 2;
scatter3(a(mask), b(mask), c(mask))
  2 Kommentare
Biswanath Mahanty
Biswanath Mahanty am 29 Jul. 2018
Thank you Walter Roberson. Your directives are great to start. However, when we are imposing mask onto a,b,c grids its a vector, not matrix. The results are fine with 3D scatter plot. But generating surface is not possible unless the a(mask), b(mask), c(mask) are reshaped into matrix.
Walter Roberson
Walter Roberson am 29 Jul. 2018
You should not generate a surface plot for this: because you want Y within -2 & +2, you are defining a thickness with potentially multiple points instead of a surface.

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Weitere Antworten (1)

Alan Weiss
Alan Weiss am 25 Jul. 2018
You might be able to formulate this as an optimization problem. Your decision variables are a, b, c. The objective (the thing to minimize) is the sum of the squares (or absolute values) of the infeasibilities: max(Y,2) - 2 and abs(min(-2,Y) + 2).
To use Optimization Toolbox, formulate your problem in terms of one variable x = [a,b,c]. Then use the fmincon solver or the lsqnonlin solver. You can include bounds on the variables using the lb and ub arguments.
Alan Weiss
MATLAB mathematical toolbox documentation

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