You can find other uses of linear programming in the data science course. Suppose the objective function Z = 40\(x_{1}\) + 30\(x_{2}\) needs to be maximized and the constraints are given as follows:\(x_{1}\) + \(x_{2}\) 122\(x_{1}\) + \(x_{2}\) 16\(x_{1}\) 0, \(x_{2}\) 0Step 1: Add another variable, known as the slack variable, to convert the inequalities into equations. Just like CPLEX, LINGO is a wholesome package including a solid language for expressing practical optimization models, a full-featured environment for feeding and editing problems, plus fast built-in solvers. If we denote the area of land planted with wheat and barley by x1 and x2 respectively, then profit can be maximized by choosing optimal values for x1 and x2. . This is the point (21, 0).
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The highlighted feasible area will look like this:Step 6: Find the coordinates of the optimum point. It is done by considering constraints for solving problems. Show that this cannot be done using the normal simplex algorithm. Naturally,X ≥ 0Y ≥ 0Since we have formulated the problem, let’s convert the problem into a mathematical form to solve it further.
The line will intersect more than one point in the feasible region. digitalvidya.
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