I was trying implement a project from GitHub about genetic algorithm and particle swarm algorithm.
But I face the next error:
Knowing that I use the same dataset in the project file. Can anyone help me solve the error?
Related
I am trying to solve a MIP problem in GAMS by using CPLEX Solver.
The nature of the problem is large which involves large number of constraints, variables and equation.
The model is successfully completed, however, it is not displaying any output result due to infeasible problem in some equations.
this is what I want from my model,
MODEL Stochastic /all/;
OPTION optcr=0;
OPTION mip=CPLEX;
SOLVE Stochastic using mip maximizing z1;
And this is what I got.
MIP status(119): integer infeasible or unbounded
Cplex Time: 0.00sec (det. 2.73 ticks)
Problem is integer infeasible.
No solution returned
I checked through the .lst file to know which equations are causing infeasibility and I found out many of them including infeasibility in my objective function.
I am not sure how can I remove infeasibility from my problem?
I would like to ask for suggestions and recommendations.
I have been to some online posts about the problem such as (https://www.researchgate.net/post/I-am-using-GAMS-in-MINLP-and-it-results-in-an-infeasible-solution-any-help), but it didn't helped though.
Note: I am using GAMS IDE version 24.
There is no general, easy solution for this problem. But since you use Cplex as your solver, you could try its IIS option (see https://www.gams.com/latest/docs/S_CPLEX.html#CPLEXiis) which can help to identify groups of conflicting constraints. That could give you at least a handle for a more detailed analysis of your problem.
I am solving a mixed-integer linear programming model on Python platform using the solver Gurobi. However, The gap of the model still keeps 100 % during the long-running time.
I am trying to use the codes to limit the running time. The solution is found, but I don't know why the gap in the model doesn't reduce.
I have attached the file below.
Could you help me to fix this problem?
Thank you very much!
The gap is defined as:
gap = |bestfound - bestbound|/|bestfound|
(see the Gurobi documentation).
The best bound in your screenshot stays at 0, so the gap does not change and remains 100%.
You could also add a small objective offset to enforce a non-zero dual bound. This will enable a more expressive gap. You could use the ObjCon model attribute to achieve this.
I am attempting to mesh a complicated design (~80,000 faces) for a microchannel heat sink, as pictured, and I would appreciate some advice. I have tried a range of different mesh controls (especially face sizing and body sizing), mesh settings and element sizes, and all have failed to produce a working mesh. The most common errors are shown in the linked picture, in particular the one regarding "The following surfaces cannot be meshed with acceptable quality. Try using a different element size or virtual topology." However, I have already reduced the element size to 2x10^-6 m, which takes two days to resolve before failure.
Unfortunately I cannot alter the geometry significantly, as it is imported from generation in SolidWORKS as either a STEP or an x.t file. As such, any advice for how I can successfully mesh the geometry for CFD analysis in FLUENT would be greatly appreciated.
I can provide more details or the geometry file itself if required.
Thanks in advance.
Meshing Attempt
Probably your cad design is not clean at all. But it is impossible to notice from this image. If you don't have control over the geometry source it is trouble. Because you might ask somebody else about check and fix something. First check you can do with your model it's trying to reduce the number of elements until the minimum possible value. Then if the mesh runs properly you can relay in the surfaces of your cad model. After that, you can refine the mesh, but the refining process is something that you have to do following some error criteria. If you are also the designer why not try to simplify a bit the geometry if you consider it is really hard to mesh? Meshing properly is a hard task, you should go step-by-step until you reach some solution. Also, you must not allow the preprocessor mesh automatically, without giving some criteria. Probably the first thing you have to answer even before apply any mesh is, what is your Reynolds number? And what is the most valuable result in which you can base the goodness of your discretization?
Thank you for your suggestions. In the end I solved the issue by importing the original mesh generated by COMSOL into SpaceClaim, then employing both the "Smooth" and "Reduce Faces" tools in tandem to simplify the geometry, before finally using SolidWORKS to turn the smoothed mesh into a solid body. This body retained many of the same features as the original, but was much less complex, having two orders of magnitude fewer faces. In turn, this permitted both meshing and heat transfer analysis in FLUENT.
I encounter some problem while running the python script on Google cloud computing instance, with python 3.6, tensorflow 1.13.1. I see several people encounter similar problems of loops in computational graph on stackoverflow. But none of it really find the culprit for it. And I observe something interesting so maybe someone experienced can figure it out.
The error message is like this:
2019-05-28 22:28:57.747339: E tensorflow/core/grappler/optimizers/dependency_optimizer.cc:704] Iteration = 0, topological sort failed with message: The graph couldn't be sorted in topological order.
2019-05-28 22:28:57.754195: E tensorflow/core/grappler/optimizers/dependency_optimizer.cc:704] Iteration = 1, topological sort failed with message: The graph couldn't be sorted in topological order.
My script for train.py will look like this:
import A,B,C
...
def main():
....
if __name__ == '__main__':
main()
So I will show my two ways to run this script:
VERSION1:
In terminal,
python3 train.py
This gives me the error like I state above. When I only use CPU, i notice it throws me something like failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected. So I add GPU to my instance but the loop in computational graph is still there.
VERSION 2(This is where weird thing happens):
I just simply copy, with nothing changed, the code in main to the jupyter notebook and run there. Then suddenly, no error occurs anymore.
I don't really know what's going on under the hood. I just notice the message at the beginning of the running is not the same between two different ways of running the code.
If you encounter the same problem, copy to jupyter notebook might help directly. I would really like share more info if someone has any ideas what might possible cause this. Thank you!
Well it turns out, no matter what, I choose a wrong way to build the graph at the beginning, which will not give the loop in my perspective. The loop error give me an idea I'm doing something wrong. But the interesting question I mentioned above is still not answered! However, I'd like to share my error so anyone see the loop error should think whether you're doing the same thing as me.
In the input_fn, I use tensor.eval() to get corresponding numpy.array in the middle to interact with data outside of that function. I choose not to use tf.data.Dataset because the whole process is complicated and I can't compress the whole thing into Dataset directly. But it turns out this approach sabotage the static computational graph design of Tensorflow. So during training, it trains on the same batch again and again. So my two cents advice is that if you want to achieve something super complex in your input_fn. It's likely you will be better off or even only doing the right thing by using the old fashioned modelling way- tf.placeholder.
I have some LVIS Lidar data in hdf5 format.
The data has Lat and Long co-ordinates, so I have been able to visualise them on a map using Basemap:
f = h5py.File('ILVIS1B_GA2016_0304_R1701_043591.h5','r')
LONG = f['/LON0/']
LAT = f['/LAT0/']
X = LONG[...]
Y = LAT[...]
m = Basemap(projection='merc',llcrnrlat=-0.5,urcrnrlat=0.5,\
llcrnrlon=9,urcrnrlon=10,lat_ts=0.25,resolution='i')
m.drawcoastlines()
m.drawcountries()
parallels = np.arange(-9.,10.,0.5)
m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(-1.,1.,0.5)
m.drawmeridians(meridians,labels=[True,False,False,True])
m.drawmapboundary(fill_color='white')
x,y = m(X, Y)
scatter = plt.scatter(x,y)
m.scatter(x,y)
plt.show()
This gets me this, where the orange bands are very dense points:
The hdf5 file also has the full waveform data for each mapped point (each datapoint is a reflection detected at the sensor, as a function of time) so that each of the orange points has data associated with it like:
Ultimately, I would like to be able to click on any of the orange points and for the subsequent waveform to be displayed. I have looked into interactive plots for this and have come across a number of libraries (mpl3d, plotly etc).
I'm having some trouble getting my head around some of these and how I can get my data into the examples - my python isn't up to this level. Does anyone have any advice on where to start? Which libraries would be best suited to this? A little help to understand the basics would be appreciated.
Apologies there is no direct question here, I'm just after some info from the knowledgable community.
The question seems to be: How do I tackle a task I have no clue how to solve?
Step 1: Search for a possible solution. It may happen that someone else has already solved your problem. This will mostly not be the case, but you may be lucky.
Step 2: Abstract the task. What would be the general problem that a lot of people might have and for which there might be a solution? Does it need to be hdf5 files? No. Is georeferencing important? Maybe, but one could neglect for the moment. Which requirements are really important, which not?
Step 3: Search again. You will have more success now for finding similar or related problems.
Step 4: Look at the tools in use. Make a list of possible tools and check against your requirements. Interactivity, Application or web-based, accuracy etc.
Step 5: Decide for one tool and go for it. Start with a general case study. Can I plot a map on the left and a graph on the right side using this tool? If not, find out why - maybe there is a general problem with this, maybe there is just an implementation detail missing. At this point you may ask a question about the case study problem, specifying the tool in use and providing the code that gives the problem. Do not think about your actual problem until this is solved.
Step 6: Proceed and try to add interactivity. Can I get something to happen when clicking? Again treat this independent of the actual problem. Search for solutions and if there none, ask a question about it.
Step 7: Proceed further up to the point where you're truely stuck. Now is the time to finally ask a question here, but with all the details that have brought you down to step 7 inside the question.