Added: 2 years ago
From: mathm09
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  • I want to watch" shortest path problem" with "floyd method". I didn't find. How can I find. do you have any videos about this

  • Is it a must that a pivot number to has a value of 1 after we have already found it? I mean why do you divide row2 by 2?

  • @glorfindel133 Yes.. at 2:14 , x1 becomes basic variable and s2 leaves basic variables (these actions are based on which was pivot column and row respectively)... since x1 turns to a basic variable, we should have value 1 where x1 (basic variables, vertical order) crosses itself (horizontal order) ... since the pivot number was 2 (initial table), we divide by 2 to get that value 1 (2nd table), but we have also to divide by 2 (apply the same operation on) the rest elements of the pivot row.

  • Lost it when we got to the 2nd Simplex tableau. T_T

  • managerial accounting

  • this video would be much better with audio...

  • This video would be much better if you had audio, and didn't move so fast. Really hard to follow with the speed...

  • @evolutionoforage

    However, a min problem, with all constraints <=, can easily have, not bounded solution (when constraints have at least one negative term) or trivial solution {0,0,0} (all constraints have only positive terms, our case study: for {1,0,0} or {0,2,0} zz is negative, so max zz is 0 for {0,0,0}).

  • @evolutionoforage

    The sign (+,-) in objective function's terms (not only in constraints) makes also a difference. min  z=60x1 - 30x2 + 20x3 ( -30 !! ) with same constraints would have another solution (not {0,0,0} from the initial Simplex table).

  • @evolutionoforage

    Note: First row in 1st table is 60 30 20 0 0 0 0 , last row in 1st table is -60 -30 -20 0 0 0 0

    and termination rule is " no <0 values in last row" (optimal solution).

    In many textbooks: First row in 1st table is 60 30 20 0 0 0 0  last row in 1st table is also 60 30 20 0 0 0 0

    and termination rule is inversed " no >0 values in last row" (optimal solution).

    Both ways, algorithm's conclusions are the same.

  • @evolutionoforage

    Sorry, not checking this email account regularly...

    Consider f(x)=x^2+3x+6 (U shape) ... min f(x) = 3.75 at x= -1.5

    Consider g(x)= -f(x) = -x^2-3x-6 (inverse U shape) ... max g(x) = -3.75 at x= -1.5

    Conclusion: min f(x)= -max g(x) = - max (-f(x))

    So, maximize zz = -60x1 -30x2 - 20x3 . x1, x2 , x3 will be the same with min z=60x1+ 30x2 + 20x3 , but optimal solution is z = -zz

    So , you start with -60 -30 -20 etc.

  • Thank you, very helpful

  • Thank you!

  • I kind of got lost there. How did you get 240 and 280 at the end. I couldn't follow the logic. Please explain. Thanks.

  • value 240 at 4:47 ...

    r5 ' = r5 - (-60) r2 ' = r5 +60 r2 ' = 0 + 60*4 = 240

    value 280 at 8:38 ...

    r5 '' = r5' - (-5) r1 '' = r5 ' +5 r1 '' = 240 + 5*8 = 240 + 40 = 280

    An alternative way to get these 2 values : sumproduct of yellow columns at right , that is (4:47) 4*60=240 (only x1 is in the basic variables) and (8:38) 2*60 + 8*20 = 120 + 160 = 280 (x1 and x3 are in the basic variables). Objective function 60x1+30x2+20x3 gets these values for solutions {4,0,0} and {2,0,8} respectively.

  • Really good video. Taught us perfectly :)

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