Tri-skill variant Simplex and strongly polynomial-time algorithm for linear programming
Abstract
The existence of strongly polynomial-time algorithm for linear programming is a cross-century international mathematical problem, whose breakthrough will solve a major theoretical crisis for the development of artificial intelligence. In order to make it happen, this paper proposes three solving techniques based on the cone-cutting theory: 1. The principle of Highest Selection; 2. The algorithm of column elimination, which is more convenient and effective than the Ye-column elimination theorem; 3. A step-down algorithm for a feasible point horizontally shifts to the center and then falls down to the bottom of the feasible region . There will be a nice work combining three techniques, the tri-skill is variant Simplex algorithm to be expected to help readers building the strong polynomial algorithms. Besides, a variable weight optimization method is proposed in the paper, which opens a new window to bring the linear programming into uncomplicated calculation.
Cite
@article{arxiv.2101.02996,
title = {Tri-skill variant Simplex and strongly polynomial-time algorithm for linear programming},
author = {P. Z. Wang and J. He and H. C. Lui and Q. W. Kong and Y. Shi and S. Z. Guo},
journal= {arXiv preprint arXiv:2101.02996},
year = {2021}
}