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马鹿算法的综述与分析。

Review and analysis for the Red Deer Algorithm.

作者信息

Zitar Raed Abu, Abualigah Laith, Al-Dmour Nidal A

机构信息

Sorbonne Center of Artificial Intelligence, Sorbonne University-Abu Dhabi, Abu Dhabi, UAE.

Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, 11953 Jordan.

出版信息

J Ambient Intell Humaniz Comput. 2023;14(7):8375-8385. doi: 10.1007/s12652-021-03602-1. Epub 2021 Nov 20.

Abstract

In this paper, the Red Deer algorithm (RDA), a recent population-based meta-heuristic algorithm, is thoroughly reviewed. The RD algorithm combines the survival of the fittest principle from the evolutionary algorithms and the productivity and richness of heuristic search techniques. Different variants and hybrids of this algorithm are presented and investigated. All the applications that were solved with this algorithm are presented. It is crucial to analyze the performance of this algorithm, therefore, the paper sheds light on the algorithm unique features and weaknesses covering the applications that are primarily suitable for it. The conclusions are presented, and further recommendations are suggested based on the review and analysis covered. The readers of this paper will have an understanding of the RD algorithm and its variants and, consequently, decide how suitable this algorithm is for their own business, research, or industrial applications.

摘要

本文对红鹿算法(RDA)进行了全面综述,该算法是一种最近基于种群的元启发式算法。RD算法结合了进化算法中的适者生存原则以及启发式搜索技术的生产率和丰富性。本文介绍并研究了该算法的不同变体和混合算法。展示了所有使用该算法解决的应用。分析该算法的性能至关重要,因此,本文阐明了该算法的独特特征和弱点,涵盖了主要适用于它的应用。给出了结论,并根据所涵盖的综述和分析提出了进一步的建议。本文的读者将了解RD算法及其变体,从而决定该算法对他们自己的业务、研究或工业应用的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad1a/8605784/40b86d77a5b8/12652_2021_3602_Fig1_HTML.jpg

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