Awesome lecture very helpful. I am student of USM Malaysia so, it's great to see like this.i feel always problem in sensitivity analysis but it's helpful me.
Thanks for uploading, I was looking for a nice introductory explanation of the dual. If I understood correctly, then at 33:04, the actual new optimum is at x=2.5, y=2.5, with a dual of -2. The optimum will still be at the intersection of the blue and green constraints (Cb and Cg), which are now 1x + 3y >= 10 2x + 2y >= 10 To calculate their intersection we can set them to equalities and do (Cg - 2Cb), giving 2x + 2y = 10 2x + 6y = 10 _____________ - 0x - 4y = -10 so y = 2.5. Plugging that back into either Cg or Cb gives x=2.5. The dual then is ((8*3 + 12*2) - (8*2.5 + 12*2.5) / 1) = (24 + 24) - (20 + 30) = 48 - 50 = -2, where P_new = 50 is the objective value for the new optimum
Very well explained , Very helpful . I have saved myself 4 hours of reading a textbook
Thank you so much.
Awesome lecture very helpful. I am student of USM Malaysia so, it's great to see like this.i feel always problem in sensitivity analysis but it's helpful me.
So nice video, I have easily understood. Thanks so much!
Everybody is coughing...... oh wait.. it was filmed in 2018. good ol days
LMAO ikr?? Now when I get a sniffle/cough and I call out or WFH with no question
Thanks for uploading, I was looking for a nice introductory explanation of the dual.
If I understood correctly, then at 33:04, the actual new optimum is at x=2.5, y=2.5, with a dual of -2.
The optimum will still be at the intersection of the blue and green constraints (Cb and Cg), which are now
1x + 3y >= 10
2x + 2y >= 10
To calculate their intersection we can set them to equalities and do (Cg - 2Cb), giving
2x + 2y = 10
2x + 6y = 10
_____________ -
0x - 4y = -10
so y = 2.5. Plugging that back into either Cg or Cb gives x=2.5.
The dual then is ((8*3 + 12*2) - (8*2.5 + 12*2.5) / 1) = (24 + 24) - (20 + 30) = 48 - 50 = -2, where P_new = 50 is the objective value for the new optimum
Thnak you for your video,Professor Geisler!
How does the sensitivity change for 3 or more variables, since we then can't find the slope? or can we?
Thank you so much for this video!
why you choose the first both equations to solve the range of optimality?
that where the Objective function slope lie in between, between the slope of first constraint and the slope of second constraint
Thanks
Thanks!
thank you!!!