Dantzig’s Simplex Algorithm is a widely used method for solving linear programming problems, which involve maximizing or minimizing a linear objective function subject to a set of linear constraints. The algorithm operates on a feasible region defined by these constraints, represented as a convex polytope in an n-dimensional space. It iteratively moves along the edges of this polytope to find the optimal vertex (corner point) where the objective function reaches its maximum or minimum value.
The steps of the Simplex Algorithm include:
The algorithm is efficient, often requiring only a few iterations to arrive at the optimal solution, making it a cornerstone in operations research and various applications in economics and engineering.
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