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Source. Theorem 6.1, p. 48, with the definition of representability on p. 48, of Shmuel Onn, Convex Discrete Optimization, arXiv:math/0703575v1 [math.OC] (20 March 2007), published in the Encyclopedia of Optimization (2009), 513--550, as identified on the source card. Labels and pages are those of the arXiv preprint. The paper presents the result as one of its references [13, 15] and gives an outline of the proof only (p. 48).
Setting
A polytope is representable as a polytope when some injection makes the coordinate-erasing projection a bijection from onto and from onto (p. 48).
Statement
Theorem 6.1 (p. 48). There is a polynomial time algorithm that, given and , with input encoded as , produces , and line-sums , and such that the polytope is representable as
The statement calls a polytope, and the outlined proof uses that it is bounded (p. 49); the paper's paraphrase before it is that any rational polytope is such a short 3-way polytope (p. 48). The overview (p. 8) states the theorem in the form that every linear integer program is polynomial time representable as a short 3-way line-sum transportation problem.
Proof pointer
Pp. 48--51, an outline in three polynomial time steps: rewrite the system with coefficients in by binary expansion of the entries; represent the result as a face of an polytope with all plane-sums fixed, some entries forced to zero, using a coordinate bound from Cramer's rule; then represent such a face as an polytope with all line-sums fixed. Complete details are in the paper's references [13, 15].
Dependencies
None within the paper. The paper derives from it Corollary 6.2 (p. 52), NP-completeness of feasibility for line-sum tables. Read depth: claims checked; the statement and the definition were read clause by clause, the outline for its structure.
Bears on
No Erdős problem in the corpus.