Hi Guys, please comment and let me know what you think about this Operations Research Open Course. Your feedback is really appreciated. If you enjoy the video, please subscribe and share. All my replies here are only related to the content in my own videos. I am afraid I won't be able to answer other questions. Thanks for your understanding.
It has been 1 year but let me explain. You just take R2, multiply it by M, then subtract that mutated R2 from R0. This is done to get a1's coefficient in R0 to 0.
@@aliosman0 No, you explained the wrong step for him, I'm confused as him and i want to know also HOW R0 went from 1 -3-M -2-2M 0 M 0 -9M (which you explained the EROs for) to 1 -2 0 0 -1 1+M 9 ?????? i couldn't figure it out please help me if you can
At time 2:20, do you mean that "if ANY artificial variable in final solution equals zero, the solution is optimal" and "if ALL artificial variables are positive, the problem is infeasible"? This is because I'm trying to reconcile these points to the decision made in time 5:35, without having to work it out.
Hi Bambo. No, All the artificial variables must be zero for the solution to be optimal. Note that excess variable e and slack variable s are not considered artificial variables in this video.
Hanan, this is because the second constraint has a ">=". We need to subtract a positive excess variable e2. You may find more info about this in "04A Linear Programming Slack & Excess Variables".
2 years have passed but: for simplex method we need the origin to be a feasible point, and in this case that is not possible, so we need to tweak the method with big M
Hi Guys, please comment and let me know what you think about this Operations Research Open Course. Your feedback is really appreciated. If you enjoy the video, please subscribe and share. All my replies here are only related to the content in my own videos. I am afraid I won't be able to answer other questions. Thanks for your understanding.
Awesome! I had lots of lessons of OR in the recent weeks and none has been as effective as this one lesson.
+1 very enlightening!
What is EROs and how do R0 goes from -3-M to -2 and -2-2M to 0?? I don't understand how R0 is being updated at 3:35
It has been 1 year but let me explain. You just take R2, multiply it by M, then subtract that mutated R2 from R0. This is done to get a1's coefficient in R0 to 0.
Elementary Row Operations(EROs)
@@aliosman0 No, you explained the wrong step for him, I'm confused as him and i want to know also HOW R0 went from 1 -3-M -2-2M 0 M 0 -9M (which you explained the EROs for) to 1 -2 0 0 -1 1+M 9 ?????? i couldn't figure it out please help me if you can
Your videos are awesome- you get straight to the point!
Thanks
In the case of maximization,we take greater value absolute negative or greater positive value
At time 2:20, do you mean that "if ANY artificial variable in final solution equals zero, the solution is optimal" and "if ALL artificial variables are positive, the problem is infeasible"? This is because I'm trying to reconcile these points to the decision made in time 5:35, without having to work it out.
Hi Bambo. No, All the artificial variables must be zero for the solution to be optimal. Note that excess variable e and slack variable s are not considered artificial variables in this video.
@@YongWang Why in the final step a2 is equal to zero?
in 3:02 could I have replaced R0 with R0 - M(R1)?
No, otherwise the coef M for the artificial variable a2 will not disappear.
Thanks!
At 5:15, how do you read the table? Where do the solution coefficients come from in the table?
In example 2 on the last slide, why don't you consider the values "2M+2" in row R0 and "-0.5" in row R2 (both in the column of x2)?
Why did you make the coeff. of e2 negative one
Hanan, this is because the second constraint has a ">=". We need to subtract a positive excess variable e2. You may find more info about this in "04A Linear Programming Slack & Excess Variables".
Thank you sir.
@@joylm9108 no problem
Why is the subscript for the artificial variable a 2? Why not a1 or a3?
because it is added to row 2?
@@ahmetensar9811 Yes. Actually, you can name it arbitrarily. But by convention, we tend to use a subscript that is the same as the row number.
but why do we need the artificial variables? couldn't we just solve the problem with just the excess (-e) in the last constraint?
2 years have passed but: for simplex method we need the origin to be a feasible point, and in this case that is not possible, so we need to tweak the method with big M
Why is it call "Big M" method?
because we use a number M which is very big.