A Polynomial Time Algorithm For 0-1 Integer Linear Programmings
G.Q. Zhang
TL;DR
This paper presents a polynomial-time algorithm for 0-1 integer linear programming that reconstructs constraints into strong cuts, claiming to solve ILPs efficiently and suggesting P=NP.
Contribution
It introduces a novel method of transforming LP constraints into strong cuts to solve 0-1 ILPs in polynomial time.
Findings
Algorithm is polynomial-time based on complexity analysis
Proposes a new approach to solving 0-1 ILPs
Claims to establish P=NP
Abstract
A polynomial-time algorithm for 0-1 integer linear programmings has been proposed. This method continues the classic idea of solving ILP with its LP relaxation. The innovation is that every constraint in the LP is reconstructed into a strong cut. Then the solution algorithm of a 0-1 ILP is developed based on the new constraints. Algorithmic complexity analysis shows that the proposed algorithm is a polynomial-time algorithm, which means that P=NP.
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Taxonomy
TopicsScheduling and Optimization Algorithms · Constraint Satisfaction and Optimization · Optimization and Packing Problems