Linear Programming: Simplex Method for Maximize π
Learn steps to solve maximization problems using the simplex method, including converting inequalities and creating initial solutions.
Solomon Getachew
48.8K views β’ Dec 3, 2021
About this video
Steps of simplex method for maximization:
Convert each inequality in the set of constraints to an equality by adding slack variables.
Create the initial simplex tableau.
Locate the most positive entry (Cj-Zj) in the bottom row to determine the pivot column.
The smallest ratios of βRHS-columnβ with their corresponding pivot column is pivot row.
Use elementary row operations so that the pivot value is 1, and all other entries in the entering column are 0. This process is called pivoting.
If all (Cj-Zj) β€ 0, this is the final table. If not, go back to Step 3 to determine the pivot column.
From the final table, the LPP has a maximum solution, which is given by the entry in the lower-right corner of the table.
Convert each inequality in the set of constraints to an equality by adding slack variables.
Create the initial simplex tableau.
Locate the most positive entry (Cj-Zj) in the bottom row to determine the pivot column.
The smallest ratios of βRHS-columnβ with their corresponding pivot column is pivot row.
Use elementary row operations so that the pivot value is 1, and all other entries in the entering column are 0. This process is called pivoting.
If all (Cj-Zj) β€ 0, this is the final table. If not, go back to Step 3 to determine the pivot column.
From the final table, the LPP has a maximum solution, which is given by the entry in the lower-right corner of the table.
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Video Information
Views
48.8K
Likes
395
Duration
38:18
Published
Dec 3, 2021
User Reviews
4.3
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