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Solving binary optimisation problems using Computational Packages

", "licence": "Creative Commons Attribution 4.0 International"}, "statement": "", "advice": "

\n

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$P-\\var{code1}\\var{code2}\\var{code3}\\var{code4}\\var{code5}\\var{code6}\\var{code7}$

\n

Solve the following binary optimisation problem using Computational Packages.

\n

{mm}: $ cx $

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Subject to:  $Ax \\le b,$ $~~ x_i \\in \\{0,1\\}$

\n

\n

where

\n

$c$ = $\\var{c11}$

\n

$b$ = $\\var{bbb}$

\n

$A$ = $\\var{A}$

\n

\n

Submitting your results:

\n
    \n
  1. Click on \"End Exam\" and \"Print this results summary\" (your problem will be extracted as a pdf file with all the necessary information/data). Do not worry about the \"Total 0/0 (0%)\" score, this pdf is only for generating a LP problem).
  2. \n
  3. Solve the problem by using any Computational Packages.
  4. \n
  5. Submit the above pdf, your code and your optimal solution (optimal $x$ and objevtive function value $cx$ that is expected to be $\\le \\var{fv}$) as part of your related OnTrack task.
  6. \n
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Solving continuous optimisation problems using Computational Packages

", "licence": "Creative Commons Attribution 4.0 International"}, "statement": "", "advice": "

\n

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Solve the following continuous optimisation problem using  Computational Packages.

\n

{mm}: $ cx $

\n

Subject to:  $Ax \\le b,$ $~~ 0 \\le x_i \\le 10, ~ for ~ all~ i.$

\n

\n

where

\n

$c$ = $\\var{c11}$

\n

$b$ = $\\var{bbb}$

\n

$A$ = $\\var{A}$

\n

\n

Submitting your results:

\n
    \n
  1. Click on \"End Exam\" and \"Print this results summary\" (your problem will be extracted as a pdf file with all the necessary information/data). Do not worry about the \"Total 0/0 (0%)\" score, this pdf is only for generating a LP problem).
  2. \n
  3. Solve the problem by using any Computational Packages.
  4. \n
  5. Submit the above pdf, your code and your optimal solution (optimal $x$ and objevtive function value $cx$ that is expected to be $\\ge \\var{fv}$) as part of your related OnTrack task. P-{x0[0]}{x0[1]}{x0[2]}{x0[3]}{x0[4]}{x0[5]}
  6. \n
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