Three products are manufactured on one machine. The preparation time of each product is 2,3 and 4 minutes respectively, and the process time of 3, 2 and 1 minutes. The benefit provided byeach product is respectively 12, 10 and 15 UM. There are 100 machine minutes and 200for its preparation. Determine the optimal number of units to manufacture of eacharticle.do it in Jupyter Notebook (.ipynb) with the code, the tables of the simplex method and the graphs of theoptimal solution.Identify the decision variables that will represent the quantity of each productto manufacture.Formulate the linear programming problem to maximize total profitsubject to the given restrictions.
Three products are manufactured on one machine. The preparation time of each product is 2,3 and 4 minutes respectively, and the process time of 3, 2 and 1 minutes. The benefit provided byeach product is respectively 12, 10 and 15 UM. There are 100 machine minutes and 200for its preparation. Determine the optimal number of units to manufacture of eacharticle.do it in Jupyter Notebook (.ipynb) with the code, the tables of the simplex method and the graphs of theoptimal solution.Identify the decision variables that will represent the quantity of each productto manufacture.Formulate the linear programming problem to maximize total profitsubject to the given restrictions.
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Three products are manufactured on one machine. The preparation time of each product is 2,
3 and 4 minutes respectively, and the process time of 3, 2 and 1 minutes. The benefit provided by
each product is respectively 12, 10 and 15 UM. There are 100 machine minutes and 200
for its preparation. Determine the optimal number of units to manufacture of each
article.
do it in Jupyter Notebook (.ipynb) with the code, the tables of the simplex method and the graphs of the
optimal solution.
Identify the decision variables that will represent the quantity of each product
to manufacture.
Formulate the linear programming problem to maximize total profit
subject to the given restrictions.
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