On the number of iterations of Karmarkar’s algorithm for linear programming. (English) Zbl 0804.90092

Summary: Karmarkar’s algorithm for linear programming was published in 1984, and it is highly important to both theory and practice. On the practical side some of its variants have been found to be far more efficient than the simplex method on a wide range of very large calculations, while its polynomial time properties are fundamental to research on complexity. These properties depend on the fact that each iteration reduces a “potential function” by an amount that is bounded away from zero, the bound being independent of all the coefficients that occur. It follows that, under mild conditions on the initial vector of variables, the number of iterations that are needed to achieve a prescribed accuracy in the final value of the linear objective functions is at most a multiple of \(n\), where \(n\) is the number of inequality constraints. By considering a simple example that allows \(n\) to be arbitrarily large, we deduce analytically that the magnitude of this complexity bound is correct. Specifically, we prove that the solution of the example of Karmarkar’s original algorithm can require about \(n/20\) iterations. Further, we find that the algorithm makes changes to the variables that are closely related to the steps of the simplex method.


90C05 Linear programming
90C60 Abstract computational complexity for mathematical programming problems
Full Text: DOI


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