差分进化策略下的数据优化:最新研究综述

Tarik Eltaeib, J. Dichter
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引用次数: 0

摘要

在优化领域,提出了各种各样的算法,差分进化(DE)是最有效的算法之一。在后者中,需要更有效和高效的技术和战略。虽然这些算法大多表现出了很好的性能,但它们仍然存在收敛速度慢的问题。本文综述了DE的所有策略、技术和一些重要算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data optimization with differential evolution strategies: A survey of the state-of-the-art
In the optimization filed, there are various proposed algorithms and Differential Evolution (DE) is one of the most effective ones. Among the latter, there is need for more effective and efficient techniques, and strategies. Although most of these algorithms have demonstrated very good performance, but they still suffer from slow convergence rate. This paper reviews the DE, all its strategies, techniques, and some important algorithms.
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