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A branch&bound algorithm for solving one-dimensional cutting stock problems exactly

Guntram Scheithauer, Johannes Terno (1995)

Applicationes Mathematicae

Many numerical computations reported in the literature show only a small difference between the optimal value of the one-dimensional cutting stock problem (1CSP) and that of the corresponding linear programming relaxation. Moreover, theoretical investigations have proven that this difference is smaller than 2 for a wide range of subproblems of the general 1CSP.

A linear programming based analysis of the CP-rank of completely positive matrices

Yingbo Li, Anton Kummert, Andreas Frommer (2004)

International Journal of Applied Mathematics and Computer Science

A real matrix A is said to be completely positive (CP) if it can be decomposed as A = BB^T, where the real matrix B has exclusively non-negative entries. Let k be the rank of A and Φ_k the least possible number of columns of the matrix B, the so-called completely positive rank (cp-rank) of A. The present work is devoted to a study of a general upper bound for the cp-rank of an arbitrary completely positive matrix A and its dependence on the ordinary rank k. This general upper bound of the cp-rank...

A logarithm barrier method for semi-definite programming

Jean-Pierre Crouzeix, Bachir Merikhi (2008)

RAIRO - Operations Research

This paper presents a logarithmic barrier method for solving a semi-definite linear program. The descent direction is the classical Newton direction. We propose alternative ways to determine the step-size along the direction which are more efficient than classical line-searches.

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