Linear Programming Calculator

Simplex is the method and linear programming is the question, so both are on this page. The two-variable tab takes up to five constraints in x and y, each of them less than, greater than or equal to a right-hand side, finds every vertex of the feasible region, evaluates the objective at each, and draws the region with the optimum marked. It reports infeasible and unbounded problems as those rather than returning a number. The simplex tab takes up to four variables and three constraints, all of the form a.x less than or equal to b with b not negative, and shows each tableau with the entering and leaving variables and the shadow prices at the end.

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Up to five constraints in x and y, each of which may be <=, >= or =. Leave a constraint with both coefficients at zero to skip it. x >= 0 and y >= 0 are always applied.

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Maximize with up to four variables and three constraints, every one of the form a.x <= b with b at zero or above. That is the case the slack basis starts feasible in, so no artificial variables are needed. Leave a row at all zeros to skip it.

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