A QUADRATICALLY CONVERGENT GLOBAL ALGORITHM FOR THE LINEARLY-CONSTRAINED MINIMUM CROSS-ENTROPY PROBLEM

Shu‐Cherng Fang

doi:10.1016/0377-2217(94)90365-4

1994-12-01

PRE

Shu‐Cherng Fang

H.-S. Jacob Tsao

DOI：10.1016/0377-2217(94)90365-4

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摘要

En 中文

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.

Keyword:

ENTROPY OPTIMIZATION

DUALITY

UNCONSTRAINED OPTIMIZATION

CURVED-SEARCH ALGORITHM

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期刊

European Journal of Operational Research

IF:

论文数:

2.2W

被引数:

6.4W

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