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This issue might be solved with a dual or simply by testing the vertices in the feasible area, but consider fixing it with the simplex algorithm.
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This type of process would also function for linear optimization complications in greater than two variables. On the other hand, these kinds of problems are more challenging to visualize with a coordinate graph, and there might see here be many more vertices to look for the optimal solution. The simplex algorithm was formulated as an productive process to resolve These types of issues.
The simplex algorithm starts by converting the constraints and objective functions into a system of equations. That is performed by introducing new variables called slack variables. Slack variables symbolize the good big difference, or slack
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