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Linear Programming Advantages in the Simplex Method

Updated July 20, 2017

The Simplex method is an algorithm that solves linear programming problems with three or more variables. It is highly efficient and used in business, science, and industry in a variety of scenarios.

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The Simplex method was an invention of Dr. George Dantzig in 1947, a replacement for other methods of solving linear programming problems. It effectively replaced them due to its power and efficiency.


For complex problems involving many variables, the Simplex method is much faster than other algorithms at solving linear systems. The Simplex method's efficiency is important for computer programming, as the need for processing power is significantly lower when using it.


If more than three variables are in the problem, graphical methods will fail, as dimensions over 3 cannot be visualised using them. The Simplex method can apply where graphical methods can't.


The Simplex method necessitates taking a set of vertices and testing them with adjacent vertices, until none are left to test. In the method you use two states. Either the function improves or remains unchanged. Any other change is ignored.


If a system is comprised of entities whose behaviour can be modelled with a linear function, you can employ the Simplex method. Systems appropriate for the Simplex method include numerous applications in economics, such as optimising the price given supply and demand, or in science, monitoring predators and prey in a given environment.

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About the Author

Leroy Walker is a freelance writer specializing in technology, programming and Web development. He currently works in the software industry. Walker attended a small New England college, where he studied computer science and mathematics.

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