I am solving an Integer program model with SCIP and I need to store the objective function value. I was wondering how I can get the objective function value after solving the IP model? can someone help me?
You can use SCIPgetPrimalbound() to get the best solution value.
Also, in the interactive shell the column "primalbound" will show the current best solution value and after the optimization process stops the primlalbound is also stated.
(Note, you might want to check whether a solution was found.)
If your problem is infeasible it 10^20 (SCIPs infinity value) is printed.
(If you want to see the objective function value and the solution values of each variable, you can enter display solution in the interactive shell, which will show all non-zeros solution values and the objective function value.)
See also http://scip.zib.de/doc/html/SHELL.php .
Related
is there any solution to solve a large system of equations in a program with the TI-nspire without typing all the variable names by hand?
For example, the function solve([1 2; 3 4]* [x; y] = 2,{x,y}) requires typing x,y manually. How is this done if the dimensions of the matrix can change?
I tried to use the function constructMat(x[i], i, j, 5, 1) which partly works but solve doesn't accept this function as variable as second argument.
Thanks for the help!!
I had this problem a while ago, i couldnt find any solution but to manually type the list of variables. Ive found the way to construct the list of unkowns (B_n):
i:=3:j:=4:B_n:=newlist(j+1) For i1,i,i+j:B_n[i1-i+1]:=expr("b"&string(i1)):endfor
with result: {b3,b4,b5,b6,b7}.
I dont remember exactly why this didnt work, i guess its the same reason (solve or zeros function will not accept this list as an argument)
I am trying to solve a problem involving the equating of sums of exponentials.
This is how I would do it hardcoded:
#NLconstraint(m, exp(x[25])==exp(x[14])+exp(x[18]))
This works fine with the rest of the code. However, when I try to do it for an arbitrary set of equations like the above I get an error. Here's my code:
#NLconstraint(m,[k=1:length(LHSSum)],sum(exp.(LHSSum[k][i]) for i=1:length(LHSSum[k]))==sum(exp.(RHSSum[k][i]) for i=1:length(RHSSum[k])))
where LHSSum and RHSSum are arrays containing arrays of the elements that need to be exponentiated and then summed over. That is LHSSum[1]=[x[1],x[2],x[3],...,x[n]]. Where x[i] are variables of type JuMP.Variable. Note that length(LHSSum)=length(RHSSum).
The error returned is:
LoadError: exp is not defined for type Variable. Are you trying to build a nonlinear problem? Make sure you use #NLconstraint/#NLobjective.
So a simple solution would be to simply do all the exponentiating and summing outside of the #NLconstraint function, so the input would be a scalar. However, this too presents a problem since exp(x) is not defined since x is of type JuMP.variable, whereas exp expects something of type real. This is strange since I am able to calculate exponentials just fine when the function is called within an #NLconstraint(). I.e. when I code this line#NLconstraint(m,exp(x)==exp(z)+exp(y)) instead of the earlier line, no errors are thrown.
Another thing I thought to do would be a Taylor Series expansion, but this too presents a problem since it goes into #NLconstraint land for powers greater than 2, and then I get stuck with the same vectorization problem.
So I feel stuck, I feel like if JuMP would allow for the vectorized evaluation of #NLconstraint like it does for #constraint, this would not even be an issue. Another fix would be if JuMP implements it's own exp function to allow for the exponentiation of JuMP.Variable type. However, as it is I don't see a way to solve this problem in general using the JuMP framework. Do any of you have any solutions to this problem? Any clever workarounds that I am missing?
I'm confused why i isn't used in the expressions you wrote. Do you mean:
#NLconstraint(m, [k = 1:length(LHSSum)],
sum(exp(LHSSum[k][i]) for i in 1:length(LHSSum[k]))
==
sum(exp(RHSSum[k][i]) for i in 1:length(RHSSum[k])))
I am newbie to fuzzing tools, and basically, I would like to use fuzzing tool to test a specific function.
Essentially, this function has three input parameter, and each parameter is a number, with range 0 to 0xffff.
I would like to use a fuzzing tool to generate random input combinations, and test the target function. However, I tried zzuf, but find that it does not have a specific setting on mutating integer value..
So I am looking for a fuzzer, that supports to only mutate integer value, within a predefined range? Could anyone give me some help on this issue? Am I clear enough? Thank you.
This can be done with many tools, among them Kitty (developed by my team).
Assuming you want to generate the number with decimal representation, the following template will generate them for you (values will be comma-separated):
from kitty.model import *
t = Template(name='function inputs', fields=[
S32(name='p1', value=1, min_value=-500, max_value=1000, encoder=ENC_INT_DEC),
Static(','),
ForEach(name='p2', mutated_field='p1',
fields=S32(value=2, min_value=-3200, max_value=5098, encoder=ENC_INT_DEC)),
Static(','),
ForEach(name='p3', mutated_field='p2',
fields=S32(value=3, min_value=0, max_value=999, encoder=ENC_INT_DEC))
])
while t.mutate():
print t.render().tobytes()
Some example results:
-1,2,3
129,1026,3
129,130,3
129,18,3
129,-3200,3
129,5098,3
129,-3199,3
129,5097,3
129,-3198,3
129,5096,3
129,3,3
129,1,3
129,4,3
129,0,3
17,1026,3
17,130,3
17,18,3
17,-3200,3
17,5098,3
17,-3199,3
I'm trying to figure out if there's a way in mathematica where I can solve for particular variables when given other variables and a set of equations. Essentially there are 6 variables, and I'm given 3 of them and have to calculate the others using these equations-
Variables-
B,Qs,f0,R,c,L
Equations-
f0=1/(2*Pi*Sqrt[L*c])
Qs=(w*L)/R
w=2*Pi*f0
B=f0/Qs
We are given the values of any 3 of those variables and have to figure out the rest using those values.
I was thinking perhaps using Eliminate but I'm not sure exactly how that would be structured as I've only used it previously with set variables that don't change and a single output.
When using the Solve function with Mathematica, you can specify for what variables you want Solve to specify the solutions. Note that Solve may not be able to find expressions in terms of these variables (if the equations you give it are contradictory or insufficient) or for all values as some functions have no inverse or only partial inverses.
Your question looks a lot like homework in Electromagnetics, but here is an example with your original problem. You will have to adapt these ideas to give to Solve the set of variables you are looking for. Also remember to use == to specify equality testing. A simple = is for immediate assignment to a variable.
Solve[{f0 == 1/(2*Pi*Sqrt[L*c]), Qs == (w*L)/R, w == 2*Pi*f0, B == f0/Qs}, {f0, B, c}]
{{f0->w/(2 [Pi]), B->w/(2 [Pi] Qs), c->L/(Qs^2 R^2)}}
In algebra if I make the statement x + y = 3, the variables I used will hold the values either 2 and 1 or 1 and 2. I know that assignment in programming is not the same thing, but I got to wondering. If I wanted to represent the value of, say, a quantumly weird particle, I would want my variable to have two values at the same time and to have it resolve into one or the other later. Or maybe I'm just dreaming?
Is it possible to say something like i = 3 or 2;?
This is one of the features planned for Perl 6 (junctions), with syntax that should look like my $a = 1|2|3;
If ever implemented, it would work intuitively, like $a==1 being true at the same time as $a==2. Also, for example, $a+1 would give you a value of 2|3|4.
This feature is actually available in Perl5 as well through Perl6::Junction and Quantum::Superpositions modules, but without the syntax sugar (through 'functions' all and any).
At least for comparison (b < any(1,2,3)) it was also available in Microsoft Cω experimental language, however it was not documented anywhere (I just tried it when I was looking at Cω and it just worked).
You can't do this with native types, but there's nothing stopping you from creating a variable object (presuming you are using an OO language) which has a range of values or even a probability density function rather than an actual value.
You will also need to define all the mathematical operators between your variables and your variables and native scalars. Same goes for the equality and assignment operators.
numpy arrays do something similar for vectors and matrices.
That's also the kind of thing you can do in Prolog. You define rules that constraint your variables and then let Prolog resolve them ...
It takes some time to get used to it, but it is wonderful for certain problems once you know how to use it ...
Damien Conways Quantum::Superpositions might do what you want,
https://metacpan.org/pod/Quantum::Superpositions
You might need your crack-pipe however.
What you're asking seems to be how to implement a Fuzzy Logic system. These have been around for some time and you can undoubtedly pick up a library for the common programming languages quite easily.
You could use a struct and handle the operations manualy. Otherwise, no a variable only has 1 value at a time.
A variable is nothing more than an address into memory. That means a variable describes exactly one place in memory (length depending on the type). So as long as we have no "quantum memory" (and we dont have it, and it doesnt look like we will have it in near future), the answer is a NO.
If you want to program and to modell this behaviour, your way would be to use a an array (with length equal to the number of max. multiple values). With this comes the increased runtime, hence the computations must be done on each of the values (e.g. x+y, must compute with 2 different values x1+y1, x2+y2, x1+y2 and x2+y1).
In Perl , you can .
If you use Scalar::Util , you can have a var take 2 values . One if it's used in string context , and another if it's used in a numerical context .