Probabilistic analysis of optimization algorithms-some aspects from a practical point of view

Author:

Borgwardt K. H.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics

Reference66 articles.

1. Adler I., Karp R., and Shamir R.: A family of simplex variants solving an m x d linear program in expected number of pivot steps depending on d only, University of California, Computer Science Division, Berkeley, December 1983.

2. Adler I., Karp R., and Shamir R.: A simplex variant solving an m x d linear program in O(min2, d 2)) expected number of pivot steps, University of California, Computer Science Division, Berkeley, 1983.

3. Adler I. and Megiddo N.: A simplex algorithm where the average number of steps is bounded between two quadratic functions of the smaller dimension, Dept. of Industrial Engineering and Operations Research, University of California, Berkeley, California, December 1983.

4. Adler, I.: The expected number of Pivots needed to solve parametric linear programs and the efficiency of the self-dual-simplex method, University of California, Dept. of IE and OR, 1983.

5. Aho A. V., Hopcroft J. E., and Ullmann J. D.: The Design and Analysis of Computer Algorithms, Addison-Wesley, Reading, Mass, 1974.

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