Article
A Quadratically Convergent Global Algorithm for the Linearly-Constrained Minimum Cross-Entropy Problem
European Journal of Operations Research
(1994)
Abstract
In this paper, we propose a curved-search algorithm for solving the cross-entropy minimization problem with linear equality constrains. The proposed algorithm converges globally to a dual optimal solution with a quadratic rate of convergence. A dual-to-primal conversion formula is provided. We also analyze the computational effort required for the algorithm and report our computational experience.
Keywords
- global algorithm,
- convergent
Disciplines
Publication Date
1994
Publisher Statement
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Citation Information
Shu-Cherng Fang and Jacob Tsao. "A Quadratically Convergent Global Algorithm for the Linearly-Constrained Minimum Cross-Entropy Problem" European Journal of Operations Research Vol. 79 Iss. 2 (1994) Available at: http://works.bepress.com/jacob_tsao/42/