Відео

That’s really kind of you to say. Thank you!

The easiest thing to do would be to add a for loop at the end of the code that loops through all the arcs. Have an if statement that says if the arc is equal to 1, print out something. Something like: for (i,j) in instance.ARCS: if instance.x[i,j]()==1: print("Travel Arc:",i,"-",j,sep=",")

Thanks for responding so quickly! I see, so it has to be done for every variable? I will absolutely give it a try, though I was hoping for something similar to option omit_zero_rows 1; as in AMPL 😅

Is the supply known or the qty from the plants known?

I would recommend within your model file using a range set. So you could do something like: model.MONTHS = RangeSet(1,timeindex.length(),1) This would create a set with the numbers 1 through the length of the number of elements in your panda data frame, then just leave the set definition out of the data file.

I don’t believe there is a third video.

@@DrKatieRIT Thanks for your response. I thought there would be a step to solve the problem.

After completing the writing of objective function and constraints you have to write few more lines as following: \\\\\\\\ data = DataPortal() data.load(filename='transportation.dat', model=model) instance = model.create_instance(data=data) optimizer = SolverFactory('gurobi') results = optimizer.solve(instance) instance.display() print(results)

Hi Adam! Great question. In the objective function we are adding up the cost of everything sent across ALL the arcs in the ENTIRE network. The double summation will accomplish this nicely because we do indeed want to sum up all the costs. In the supply constraints we want to make several distinct constraints, in this particular problem we want to make 1 constraint for each power plant that says "If I add up everything leaving this one particular power plant, I want to make sure it exactly equals the supply at this particular power plant." Passing in "i" to the supply function is the part that tells pyomo which supply node we are making a constraint for. We want to do them one at a time. Inside the supply constraint we only want to sum over the index j, in this case cities, because we want to hold the power plant constant for a single supply constraint, and just add up all the demand that is leaving a single plant and going to each of the cities. So a supply constraint for plant 1 would look something like: S11+S12+S13+S14 ==35. Pyomo would also make these other two constraints: S21+S22+S23+S34==50 S31+S32+S33+S34==40 If we did what you suggest and used a double summation in the constraint, and did not pass in a power plant i to the constraint function, pyomo would create the following single constraint: S11+S12+S13+S14+S21+S22+S23+S24+S31+S32+S33+S34==35+50+40 (Not even sure what you'd put on the right hand side because this doesn't make sense). This lumped together version of the supply constraints won't work properly. For example, you could have S11 = 125, and all the other Sij =0. The constraint would be satisfied, but we know this is impossible because Plant 1 doesn't even have 125 units of power to send, and plants 2 and 3 are sending nothing, but we also know that is against the rules too. So we must make one supply constraint for each supply node to ensure the node sends all its supply, and the way the problem is formulated in the example accomplishes this. Hope this helps.

Yes and know. You can definitely hire "part time workers", so we'll assume that is the case for this problem.

Hi Ali, I'm sure I have an example somewhere of an equality constraint, check out the transportation problems they for sure have one. But in the meantime, when you have an equality constraint instead of "<=" you need two equal signs "==". That tells python to do a comparison rather than set a variable value.

This video has equality constraints: ua-cam.com/video/b8YfCIZY2xI/v-deo.html

Hi James! Making those syntax mistakes and fixing them is part of the learning process. If you ever get too stuck just reach out and I'd be happy to help.

Thanks Raymund! Glad I could help.

Hi Juan! Check out this video here: ua-cam.com/video/IZkHhq71myU/v-deo.html This one shows an example of an objective function with two summations, for three you follow the same pattern, except you just add in one more "for k in SETWHATEVER" at the end. Hope this helps. -Dr. Katie

Hello Doc. You are the best. I give it to you! Teachers are rare, yours is exceptional. I can't evbe figure out how you are able to do it. You are literally teaching us python and Pyomo at the same time and you make it so so easy and simple. Thanks so so much ❤

I’m not sure what you mean. Can you explain your error a bit more?

Thank you!

@@DrKatieRIT Could I possibly use it for illustration of my abstract course of optimization methods?

@@malgosianowak You can use my videos for whatever you'd like, just please provide acknowledgment, and links to these videos.

@@DrKatieRIT Thank you! I will.

@@DrKatieRIT If you gave me your family name, the credentials would look better. (If you think it's a good idea) I could not find you on RIT. :)

Glad you found a solution!!!!!

Gracias!

These constraints are easiest to understand if you make yourself a concrete example. For instance, what would be the average quality of orange juice if you had 5 quality 6 oranges and 3 quality 9 oranges? It would be (6+6+6+6+6+9+9+9)/8 = 7.125. This is just (6* # of quality 6 + 9 * # quality 9) / (Total Oranges) = (6*5+9*3)/(5+3) = 7.125. Once you understand how to find the average of a group of things, the rest is just simplifying the constraint so that it doesn't involve division which is a non-linear operation.

Errors in these models can be finicky and hard to find. The error messages are often not particularly helpful either. Check the parameter for salaryExp matches in both your model and data file. Make sure salaryExp has no sets listed in its declaration. Finally, I’d be happy to take a look at your files if you use Google colab and share them with me.

All set! You were missing the () after model = AbstractModel, is should say model=AbstractModel(). Assuming your data file is correct (I had to use my own), everything will work fine once you add in those (). If it doesn't work, take a look at your data file.

@@DrKatieRIT I really appreciate your prompt solution. Yeah, it is working now. You are awesome.

Sure. What are you trying to do?

@@katiemcconky938 I am trying to solve the transportation kind of problem which is mixed integer quadratic problem. I have solved problem with Gurobi solver , now wanted same to pyomo as script writing is somewhat different I need help in writing the first constraint or any expression which willl help me to understand the all pyomo functionality, then later I will write my self. If you could help me would be great help for me. You can suggest your availability and you can share link to join meeting.

Thanks! 😄